From 03b68fcff410f77c036f292e6a8994c7c2836423 Mon Sep 17 00:00:00 2001 From: Philip Manke Date: Wed, 20 Aug 2025 17:32:00 +0200 Subject: [PATCH 01/11] Add examples 1, 2 and 3 --- notebooks/Example_1_Take_Snapshot.ipynb | 218 ++++++++++++ notebooks/Example_2_Load_Measurement.ipynb | 272 ++++++++++++++ notebooks/Example_3_Reprocess.ipynb | 395 +++++++++++++++++++++ 3 files changed, 885 insertions(+) create mode 100644 notebooks/Example_1_Take_Snapshot.ipynb create mode 100644 notebooks/Example_2_Load_Measurement.ipynb create mode 100644 notebooks/Example_3_Reprocess.ipynb diff --git a/notebooks/Example_1_Take_Snapshot.ipynb b/notebooks/Example_1_Take_Snapshot.ipynb new file mode 100644 index 0000000..9fc5582 --- /dev/null +++ b/notebooks/Example_1_Take_Snapshot.ipynb @@ -0,0 +1,218 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "91abd7ea-4c7e-4eb4-97d1-4746e9d24212", + "metadata": {}, + "source": [ + "# Cuvis Python SDK Example 1\n", + "## Connect to camera and record a measurement\n", + "\n", + "This example provides a minimal starting point to allow you to get a camera and data acquisition running.\n", + "\n", + "**Used principles:**\n", + " - *AcquisitionContext* for camera control and data acquisition\n", + " - *SessionFile* as camera calibration file\n", + " - *CubeExporter* for saving measurements\n", + "\n", + "**Step-by-Step overview for this example:**\n", + " 1. Import and initialize Cuvis SDK\n", + " 2. Load the calibration file for your camera using *SessionFile*\n", + " 3. Connect and initialize your camera using the *AcquisitionContext*\n", + " 4. Acquire a measurement\n", + " 5. Save the measurement to disk using the *CubeExporter*\n", + "\n", + "**Prerequisites to running this example:**\n", + " - Have a camera connected\n", + " - Have the camera calibration file (*SN*.cu3c) ready\n", + " - Have the Cuvis SDK installed\n", + " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3391452-d716-4fb2-8977-fa95b09b54ff", + "metadata": {}, + "outputs": [], + "source": [ + "# If the import of cuvis fails, the most common cause is a mismatch between\n", + "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", + "# Try re-installing both and make sure that the version numbers match exactly\n", + "import cuvis\n", + "import time\n", + "print(\"Cuvis Python SDK Example 1\")\n", + "\n", + "# Initialize the Cuvis SDK using a settings-directory\n", + "# This is optional (all settings have defaults),\n", + "# but enables you to optimize Cuvis' performance on your system using the settings\n", + "# Your camera and the default Cuvis installation both provide these settings files\n", + "print(\"Initializing Cuvis\")\n", + "cuvis.General.init(\"./settings\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d345b826-29ba-4090-a7fa-4a016bd62905", + "metadata": {}, + "outputs": [], + "source": [ + "# Snapshot setup / User input\n", + "# Enter your data here!\n", + "snapshot_integration_time_ms = 100\n", + "save_directory = \"./data\"\n", + "camera_serial_number_str = \"ASR5232501\"\n", + "\n", + "camera_calibration_file_path = F\"./factory/{camera_serial_number_str}.cu3c\"" + ] + }, + { + "cell_type": "markdown", + "id": "abc495f9-4143-4383-87d4-8fde6b79438f", + "metadata": {}, + "source": [ + "#### Calibration Files (.cu3c)\n", + "The **.cu3c** camera calibration file format is a special form of the SessionFile format **.cu3s**\n", + "\n", + "It is thus used as a calibration file and usually contains (among other things):\n", + " - The actual encrypted camera calibration file\n", + " - A spectral radiance calibration file\n", + " - Test references (Dark and White)\n", + " - A standard camera recording configuration (framerate, integration time, etc.)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "34fdcae0-4b4b-49a3-b426-8bfa78f3d716", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Load camera calibration file\")\n", + "calib = cuvis.SessionFile(camera_calibration_file_path)" + ] + }, + { + "cell_type": "markdown", + "id": "e89674e2-697d-40f0-940f-850ef34d55d7", + "metadata": {}, + "source": [ + "#### Cube Exporter\n", + "To save measurements in the Cubert file format *SessionFile* (.cu3s), use the *CubeExporter*.\n", + "Using *SessionFiles* to save measurements, is highly recommended, as it can store multiple raw measurements, reference measurements and meta-data\n", + "all in one file, allowing you to re-process the measurements after the fact.\n", + "This enables you to fine-tune the final product, convert the output format and even fix some mistakes made during data acquisition." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "05024d39-f138-42c7-abdc-9cd0a5c5b581", + "metadata": {}, + "outputs": [], + "source": [ + "# Setup the Cube Exporter for saving the measurements to disk in the SessionFile format (.cu3s)\n", + "print(\"Create CubeExporter\")\n", + "save_config = cuvis.FileWriteSettings.SaveArgs(export_dir=save_directory)\n", + "exporter = cuvis.CubeExporter(save_config)" + ] + }, + { + "cell_type": "markdown", + "id": "1a6f730c-2bbe-46b1-8d53-7ef351620ae6", + "metadata": {}, + "source": [ + "#### Acquisition Context\n", + "The *Acquisition Context* is your interface to control the camera and all aspects of the data acquisition.\n", + "\n", + "Initialize it using a *SessionFile* object, then set the recording parameters and start an acquisition.\n", + "As soon as the **AcquisitionContext** is created, it will try to establish a connection with the camera.\n", + "\n", + "Here, the \"Software\" operation mode is used to enable data acquisition using a software trigger.\n", + "This is also called snapshot mode.\n", + "\n", + "*Please note:*\n", + "The *AcquisitionContext* will **only** connect to the **exact** camera of the same serial number matching the calibration file!\n", + "All other cameras/devices are ignored." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b47e7223-b588-4b4d-8059-f15b44c8cfb2", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Loading Acquisition Context\")\n", + "acq = cuvis.AcquisitionContext(calib)\n", + "\n", + "# Wait for camera connection to be established\n", + "print(\"Connecting with camera\")\n", + "while(not acq.ready):\n", + " time.sleep(1)\n", + " print(\".\", end=\"\")\n", + "print(\"\\nCamera connected!\")\n", + "\n", + "# Set camera to software trigger\n", + "acq.operation_mode = cuvis.OperationMode.Software\n", + "acq.integration_time = snapshot_integration_time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "99a6438c-70b7-4403-9b61-44385ff32a0e", + "metadata": {}, + "outputs": [], + "source": [ + "# Optional: Name the recording\n", + "acq.session_info = cuvis.SessionData(\"My_Measurement\", 0, 0)\n", + "\n", + "# With the camera connection established, a measurement can be triggered using the capture() method.\n", + "# This returns an AsyncMesu object\n", + "async_mesu = acq.capture()\n", + "\n", + "# To get the actual measurement, wait on the AsyncMesu using the get() method.\n", + "mesu, status = async_mesu.get(timeout_ms=5000)\n", + "print(F\"Measurement reports: {status}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e6633d5-b1ed-4570-a1b6-5ed1b2dec105", + "metadata": {}, + "outputs": [], + "source": [ + "# Export the measurement\n", + "if status == cuvis.Async.AsyncResult.done:\n", + " exporter.apply(mesu)\n", + " print(\"Measurement exported!\")\n", + "else:\n", + " print(\"Something went wrong!\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/Example_2_Load_Measurement.ipynb b/notebooks/Example_2_Load_Measurement.ipynb new file mode 100644 index 0000000..8c52488 --- /dev/null +++ b/notebooks/Example_2_Load_Measurement.ipynb @@ -0,0 +1,272 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "df14d205-d2d9-4076-9e5d-0449e95b87a7", + "metadata": {}, + "source": [ + "# Cuvis Python SDK Example 2\n", + "## Load and analyse a recorded measurement\n", + "\n", + "In this example an already recorded measurement (SessionFile .cu3s) is loaded.\n", + "The measurement's data and meta-data are accessed. \n", + "\n", + "**Used principles:**\n", + " - *SessionFile* to load a recorded measurement\n", + " - *Measurement* to access the SessionFiles data and meta-data\n", + "\n", + "**Step-by-Step overview for this example:**\n", + " 1. Import and initialize Cuvis SDK\n", + " 2. Load the recorded measurement file using *SessionFile*\n", + " 3. Access meta-data about the recording *session*\n", + " 4. Extract a *Measurement* from the *SessionFile*\n", + " 5. Access data and meta-data from a single *Measurement*\n", + "\n", + "**Prerequisites to running this example:**\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s)\n", + " - Have the Cuvis SDK installed\n", + " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5b90c64f-97c1-4161-9663-24842475a747", + "metadata": {}, + "outputs": [], + "source": [ + "# If the import of cuvis fails, the most common cause is a mismatch between\n", + "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", + "# Try re-installing both and make sure that the version numbers match exactly\n", + "import cuvis\n", + "import time\n", + "from matplotlib import pyplot as plt\n", + "print(\"Cuvis Python SDK Example 2\")\n", + "\n", + "# Initialize the Cuvis SDK using a settings-directory\n", + "# This is optional (all settings have defaults),\n", + "# but enables you to optimize Cuvis' performance on your system using the settings\n", + "# Your camera and the default Cuvis installation both provide these settings files\n", + "print(\"Initializing Cuvis\")\n", + "cuvis.General.init(\"./settings\")" + ] + }, + { + "cell_type": "markdown", + "id": "a62ad76d-c8b0-4e3e-a3c9-f79288561f26", + "metadata": {}, + "source": [ + "#### SessionFile\n", + "A SessionFile is a Cubert-proprietary container file format for storing measurement data from Cubert cameras.\n", + "It simplifies dealing with the calibration files, reference measurement and actual measurements by merging everything into a single file.\n", + "\n", + "**A SessionFile can contain:**\n", + " - One or more *Measurements*\n", + " - Reference Measurements (Dark, White, Distance, ...) (normally one per type)\n", + " - Camera calibration file and Spectral Radiance calibration file\n", + " - Meta-data about the recording settings (frame-rate, session name, etc.)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b09c072a-9665-4398-a2bd-9563814a275f", + "metadata": {}, + "outputs": [], + "source": [ + "# Enter a path applicable to your setup here\n", + "session_file_path = \"D:/TestMesus/Aquarium/Auto_004.cu3s\"\n", + "\n", + "# Load the SessionFile\n", + "print(F\"Loading Session File '{session_file_path}'\")\n", + "session = cuvis.SessionFile(session_file_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3972f90-efea-4a9c-8301-b30274482ef7", + "metadata": {}, + "outputs": [], + "source": [ + "# Read and output some session file meta-data\n", + "print(F\"Session File '{session_file_path}' meta-data:\")\n", + "\n", + "print(F\"Number of measurements: {session.get_size()}\")\n", + "\n", + "print(\"Recorded with operation mode: \", end=\"\")\n", + "recording_mode = session.operation_mode\n", + "if recording_mode == cuvis.OperationMode.Software:\n", + " print(\"Software / Snapshot\")\n", + "elif recording_mode == cuvis.OperationMode.Internal:\n", + " print(\"Internal / Video\")\n", + "else:\n", + " print(\"External / Hardware Trigger\")\n", + "\n", + "if recording_mode == cuvis.OperationMode.Internal:\n", + " print(F\"Session recorded at a framerate of: {session.fps}\")\n", + "\n", + "print(F\"Session File stores {session.get_size(cuvis.SessionItemType.references)} reference measurements\")" + ] + }, + { + "cell_type": "markdown", + "id": "d1cbc9bd-5046-42f6-bdbe-b1cf76be9fdb", + "metadata": {}, + "source": [ + "#### Measurement\n", + "The *Measurement* class is the storage container for the actual hyperspectral data, along with more specific meta-data - things that can change from measurement to measurement (eg. integration time).\n", + "\n", + "**A Measurement can contain:**\n", + " - Multiple image data\n", + " - A hyperspectral data cube\n", + " - \"Links\" to reference measurements\n", + " - Recording settings\n", + " - Meta-data about the state of the camera\n", + " - Meta-data about the software used to capture the measurement\n", + " - Meta-data about the quality of the measurement\n", + "\n", + "*Please note:* The hyperspectral cube is not always present. Processing the measurement to generate the hyperspectral cube is a compute-intensive step and is thus only done on-demand! By default, measurements are stored without the cube, but with all necessary data to generate it, to speed up saving and save on disk space (this shrinks measurements on average by about 50%)! " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "17152989-8f61-4c43-810c-9651bc6bc9ca", + "metadata": {}, + "outputs": [], + "source": [ + "# Fetch the first measurement from the session file\n", + "measurement = session.get_measurement(0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c6f1d9ac-6b4f-4db6-847f-33ade9f79e5d", + "metadata": {}, + "outputs": [], + "source": [ + "# Read and print some meta-data from the measurement\n", + "print(F\"Measurement meta-data for measurement {measurement.name}:\")\n", + "\n", + "print(F\"Captured at: {measurement.capture_time}\")\n", + "print(F\"Captured with exposure / integration time of: {measurement.integration_time} ms\")\n", + "print(F\"Captured with camera: {measurement.product_name} - {measurement.serial_number}\")\n", + "print(F\"Captured with software version: {measurement.assembly}\")\n", + "print(F\"Captured to: {measurement.path}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a550f1cf-a830-481f-9167-c85f98857da2", + "metadata": {}, + "outputs": [], + "source": [ + "# Access some meta-data from the sensor of the camera at the time of recording.\n", + "# The raw sensor image of the hyperspectral sensor is called \"IMAGE\" by convention.\n", + "# Each sensors meta-data is the sensor name + \"_info\" suffix.\n", + "# You can iterate over the measurements data attribute to see all available data fields\n", + "sensor_data = measurement.data[\"IMAGE_info\"]\n", + "print(F\"Sensor pixel format: {camera_data.pixel_format}\")\n", + "print(F\"Sensor readout timestamp: {camera_data.readout_time}\")\n", + "print(F\"Sensor gain value: {camera_data.gain}\")\n", + "print(F\"Raw sensor size (WxH): ({camera_data.width}, {camera_data.height}) pixel\")\n", + "print(F\"Sensor temperature: {camera_data.temperature} °C\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f684b471-3486-4842-80b5-a55e6b5c8629", + "metadata": {}, + "outputs": [], + "source": [ + "# Access the hyperspectral cube\n", + "\n", + "# If the cube is not generated, compute it now\n", + "# The Processing Context is explained in detail in example 3\n", + "if measurement.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(measurement)\n", + "\n", + "cube = measurement.cube" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41fbf383-305c-48c3-922a-b929dcbd4350", + "metadata": {}, + "outputs": [], + "source": [ + "# Access some fundamental information about the cube\n", + "print(F\"Cube wavelength range: {cube.wavelength[0]}nm to {cube.wavelength[-1]}nm\")\n", + "print(F\"Cube spatial resolution (WxH): ({cube.width}, {cube.height}) pixel\")\n", + "print(F\"Cube spectral resolution: {cube.channels} channels @ ~{(cube.wavelength[-1] - cube.wavelength[0]) / cube.channels :.1f}nm per channel\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "912bafa6-dc2c-4a48-a0fe-6b81ab3d7b33", + "metadata": {}, + "outputs": [], + "source": [ + "# Access a point spectrum (center pixel)\n", + "x = cube.width // 2\n", + "y = cube.height // 2\n", + "spectrum = cube.array[y,x,:]\n", + "\n", + "plt.figure()\n", + "plt.plot(cube.wavelength, spectrum)\n", + "plt.xlabel(\"Wavelength\")\n", + "plt.ylabel(\"Counts\")\n", + "plt.title(f\"Spectrum at (x={x}, y={y})\")\n", + "plt.grid(True, alpha=0.3)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23f26a05-3214-4af2-adf6-da60e5ee8155", + "metadata": {}, + "outputs": [], + "source": [ + "# Access a single channel (center channel)\n", + "c = cube.channels // 2\n", + "channel_image = cube.array[:,:,c]\n", + "\n", + "plt.figure()\n", + "im = plt.imshow(channel_image, cmap=\"gray\")\n", + "plt.title(f\"Channel {c}\")\n", + "plt.colorbar(im, fraction=0.046, pad=0.04)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/Example_3_Reprocess.ipynb b/notebooks/Example_3_Reprocess.ipynb new file mode 100644 index 0000000..b690338 --- /dev/null +++ b/notebooks/Example_3_Reprocess.ipynb @@ -0,0 +1,395 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "53848df6-126d-4ed1-bdea-e52616268b2b", + "metadata": {}, + "source": [ + "# Cuvis Python SDK Example 3\n", + "## Load and reprocess a recorded measurement\n", + "\n", + "In this example an already recorded measurement (SessionFile .cu3s) is loaded.\n", + "The measurement is reprocessed into different processing modes, explaining their differences.\n", + "\n", + "**Used principles:**\n", + " - *SessionFile* to load a recorded measurement\n", + " - *Measurement* to access the SessionFiles data and meta-data\n", + " - *ProcessingContext* to generate hyperspectral cubes using different processing modes\n", + "\n", + "**Step-by-Step overview for this example:**\n", + " 1. Import and initialize Cuvis SDK\n", + " 2. Load the recorded measurement file using *SessionFile*\n", + " 3. Extract a *Measurement* from the *SessionFile*\n", + " 4. Initialize a *ProcessingContext* from a *SessionFile*\n", + " 5. Use *ProcessingContext* to generate hyperspectral cubes\n", + "\n", + "**Prerequisites to running this example:**\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s)\n", + " - Have a recorded White and Dark reference measurement\n", + " - Have the Cuvis SDK installed\n", + " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ece811fb-7ad0-4dfe-b2f9-586341f1610f", + "metadata": {}, + "outputs": [], + "source": [ + "# If the import of cuvis fails, the most common cause is a mismatch between\n", + "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", + "# Try re-installing both and make sure that the version numbers match exactly\n", + "import cuvis\n", + "import time\n", + "from matplotlib import pyplot as plt\n", + "import numpy as np\n", + "print(\"Cuvis Python SDK Example 3\")\n", + "\n", + "# Initialize the Cuvis SDK using a settings-directory\n", + "# This is optional (all settings have defaults),\n", + "# but enables you to optimize Cuvis' performance on your system using the settings\n", + "# Your camera and the default Cuvis installation both provide these settings files\n", + "print(\"Initializing Cuvis\")\n", + "cuvis.General.init(\"./settings\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cf42d3ed-9fd1-4170-9802-cb009cbecf81", + "metadata": {}, + "outputs": [], + "source": [ + "# Enter paths applicable to your setup here\n", + "session_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", + "dark_reference_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", + "white_reference_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", + "\n", + "# Load the SessionFile\n", + "print(F\"Loading Session File '{session_file_path}'\")\n", + "session = cuvis.SessionFile(session_file_path)\n", + "# Fetch the first measurement from the session file\n", + "measurement = session.get_measurement(0)\n", + "\n", + "# Load dark reference measurement\n", + "print(F\"Loading Dark reference file '{dark_reference_file_path}'\")\n", + "dark_sess = cuvis.SessionFile(dark_reference_file_path)\n", + "if (dark_mesu := dark_sess.get_reference(0, cuvis.ReferenceType.Dark)) is not None:\n", + " print(\"Using Dark reference from Session File\") \n", + "else:\n", + " print(\"Using first measurement as Dark reference\") \n", + " dark_mesu = dark_sess.get_measurement(0)\n", + "\n", + "# Load white reference measurement\n", + "print(F\"Loading White reference file '{white_reference_file_path}'\")\n", + "white_sess = cuvis.SessionFile(white_reference_file_path)\n", + "if (white_mesu := white_sess.get_reference(0, cuvis.ReferenceType.White)) is not None:\n", + " print(\"Using White reference from Session File\") \n", + "else:\n", + " print(\"Using first measurement as White reference\") \n", + " white_mesu = white_sess.get_measurement(0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4379cbf0-5cb1-47ef-aa42-560ff3e53fa2", + "metadata": {}, + "outputs": [], + "source": [ + "# Helper functions\n", + "\n", + "# Read and print processing mode of the measurement\n", + "def print_processing_mode(measurement):\n", + " procmode = measurement.processing_mode\n", + " if procmode == cuvis.ProcessingMode.Preview:\n", + " print(\"Measurement does not have a hyperspectral cube: Preview Mode\")\n", + " elif procmode == cuvis.ProcessingMode.Raw:\n", + " print(\"Measurement has a hyperspectral cube with raw counts: Raw Mode\")\n", + " elif procmode == cuvis.ProcessingMode.DarkSubtract:\n", + " print(\"Measurement has a hyperspectral cube with raw counts: Dark Subtract Mode\")\n", + " elif procmode == cuvis.ProcessingMode.Reflectance:\n", + " print(\"Measurement has a hyperspectral cube with reflectance values: Reflectance Mode\")\n", + " elif procmode == cuvis.ProcessingMode.SpectralRadiance:\n", + " print(\"Measurement has a hyperspectral cube with Spectral Radiance values: Spectral Radiance Mode\")\n", + " else:\n", + " print(\"Unknown processing mode\")\n", + "\n", + "def show_spectrum_and_channel(measurement):\n", + " cube = measurement.cube\n", + " x = cube.width // 2\n", + " y = cube.height // 2\n", + " c = cube.channels // 2\n", + "\n", + " procmode = measurement.processing_mode\n", + " if procmode == cuvis.ProcessingMode.Preview:\n", + " print(\"Measurement does not have a hyperspectral cube: Preview Mode\")\n", + " return\n", + " elif procmode in (cuvis.ProcessingMode.Raw, cuvis.ProcessingMode.DarkSubtract):\n", + " ylabel = \"Counts\"\n", + " elif procmode == cuvis.ProcessingMode.Reflectance:\n", + " ylabel = \"Reflectance [%]\"\n", + " elif procmode == cuvis.ProcessingMode.SpectralRadiance:\n", + " ylabel = \"Spectral Radiance [W / m² / sr / µm]\"\n", + " else:\n", + " print(\"Unknown processing mode\")\n", + " return\n", + " \n", + " fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n", + "\n", + " # Spectrum at (x, y)\n", + " spectrum = cube.array[y,x,:]\n", + " if procmode == cuvis.ProcessingMode.Reflectance:\n", + " spectrum = np.array(spectrum, dtype=np.float32)\n", + " spectrum /= 100\n", + " ax0.plot(cube.wavelength, spectrum)\n", + " ax0.set_xlabel(\"Wavelength\")\n", + " ax0.set_ylabel(ylabel)\n", + " ax0.set_title(F\"Spectrum at (x={x}, y={y})\")\n", + " ax0.grid(True, alpha=0.3)\n", + "\n", + " # Single channel image\n", + " channel_image = cube.array[:,:,c]\n", + " im = ax1.imshow(channel_image, cmap=\"gray\")\n", + " ax1.set_title(F\"Channel {c}\")\n", + " fig.colorbar(im, ax=ax1, fraction=0.046, pad=0.04)\n", + "\n", + " return fig, (ax0, ax1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25d04ffd-104e-445b-b29b-422f1954a561", + "metadata": {}, + "outputs": [], + "source": [ + "print_processing_mode(measurement)" + ] + }, + { + "cell_type": "markdown", + "id": "f8279487-1a91-4b7d-9859-25ac38b5382f", + "metadata": {}, + "source": [ + "#### Processing Context\n", + "The *ProcessingContext* is the interface that enables computing a hyperspectral cube from a measurement.\n", + "A camera calibration file is required to initialize the *ProcessingContext*, as each Cubert camera is individually calibrated to provide the most accurate spectral information.\n", + "As a SessionFile contains the camera calibration, it is used to construct the *ProcessingContext*.\n", + "\n", + "To generate a hyperspectral cube, the *ProcessingContext* is **applied** to the *Measurement*. The *Measurement* is modified **in-place** and now contains a cube.\n", + "\n", + "To select the processing mode, write the **processing_mode** attribute.\n", + "\n", + "When initializing a *ProcessingContext* from a *SessionFile*, the reference *Measurements* stored in the *SessionFile* are automatically loaded and set within the *ProcessingContext*.\n", + "Using the method *set_reference*, different measurements can be set for each reference type." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "963f957f-d17c-40e6-aa35-eed218de4c51", + "metadata": {}, + "outputs": [], + "source": [ + "processing_context = cuvis.ProcessingContext(session)" + ] + }, + { + "cell_type": "markdown", + "id": "75543c76-3498-4a71-834c-9341736aeb3d", + "metadata": {}, + "source": [ + "#### Processing Mode RAW\n", + "The mode *RAW* is the most basic processing applied to generate a hyperspectral cube.\n", + "No references are necessary for this mode; it also provides the least refined data.\n", + "The data is measured in sensor counts, no physical unit can be assigned to this.\n", + "The cube data is provided as an integer format.\n", + "Either unsigned 8 bit, if the sensor pixel format is Mono8, else unsigned 16 bit." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea4bcf06-391a-4cfe-92ec-cef635a99fa4", + "metadata": {}, + "outputs": [], + "source": [ + "# Set processing mode\n", + "processing_context.processing_mode = cuvis.ProcessingMode.Raw\n", + "\n", + "# Compute a cube in Raw mode for the measurement\n", + "processing_context.apply(measurement)\n", + "# Show data\n", + "print_processing_mode(measurement)\n", + "show_spectrum_and_channel(measurement)" + ] + }, + { + "cell_type": "markdown", + "id": "01239819-722d-45ad-adc8-39937c875d11", + "metadata": {}, + "source": [ + "#### Processing Mode Dark Subtract\n", + "The mode *Dark Subtract* is similar to *RAW*, as it also measures the data in sensor counts.\n", + "A Dark reference is used in the computation for this mode to mitigate the effect of inherent sensor noise, refining the data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "698ede88-f0ad-4274-8d56-d73338fda2bd", + "metadata": {}, + "outputs": [], + "source": [ + "# Set processing mode\n", + "processing_context.processing_mode = cuvis.ProcessingMode.DarkSubtract\n", + "\n", + "# Set dark reference\n", + "processing_context.set_reference(dark_mesu, cuvis.ReferenceType.Dark)\n", + "\n", + "# Compute a cube in DarkSubtract mode for the measurement\n", + "processing_context.apply(measurement)\n", + "# Show data\n", + "print_processing_mode(measurement)\n", + "show_spectrum_and_channel(measurement)" + ] + }, + { + "cell_type": "markdown", + "id": "440b2d82-8bb3-4674-82a7-a50bb736e78f", + "metadata": {}, + "source": [ + "#### Processing Mode Reflectance\n", + "The mode *Reflectance* changes how the cube is generated and its data type.\n", + "The cube now provides data in the form of reflected light as a percentage.\n", + "A Dark and a White reference are used to compute this percentage, ie. 100% reflectance means that the data at this point is as bright as the White reference.\n", + "\n", + "*Please note:*\n", + "The cube data are still provided in an integer format (unsigned 16 bit) to speed up processing and reduce storage.\n", + "The fixed-point format is defined as such:\n", + " - 0 = 0% Reflectance (as bright as Dark reference)\n", + " - 10000 = 100% Reflectance (as bright as White reference)\n", + " - 30000 = 300% Reflectance (3 times as bright as White reference)\n", + " - 60000 = 600% Reflectance (6 times as bright as White reference)\n", + " - etc." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "583d9592-8db3-4e49-96ce-f6d25ce57ffe", + "metadata": {}, + "outputs": [], + "source": [ + "# Set processing mode\n", + "processing_context.processing_mode = cuvis.ProcessingMode.Reflectance\n", + "\n", + "# Set references\n", + "processing_context.set_reference(dark_mesu, cuvis.ReferenceType.Dark)\n", + "processing_context.set_reference(white_mesu, cuvis.ReferenceType.White)\n", + "\n", + "# Compute a cube in Reflectance mode for the measurement\n", + "processing_context.apply(measurement)\n", + "# Show data\n", + "print_processing_mode(measurement)\n", + "show_spectrum_and_channel(measurement)" + ] + }, + { + "cell_type": "markdown", + "id": "115a9cc5-1108-4b8d-9ec7-068d3b9c7657", + "metadata": {}, + "source": [ + "#### Processing Mode Spectral Radiance\n", + "The mode *Spectral Radiance* changes how the cube is generated and its data type.\n", + "The cube now provides data in the form of a physical unit: W / m² / sr / µm\n", + "\n", + "A Dark reference and a special Spectral Radiance reference are used to compute this.\n", + "\n", + "The Spectral Radiance reference is created by default by Cubert using calibrated measurement equipment during camera build-up and calibration.\n", + "It is contained in the camera calibration file.\n", + "For older cameras it used to be provided as the file *SpRad.cu3* and may not have been delivered for your camera.\n", + "\n", + "The cube data are provided in a floating point format (float 32 bit)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ef2f20c-c456-4284-8f14-23faf79a2085", + "metadata": {}, + "outputs": [], + "source": [ + "# Set processing mode\n", + "processing_context.processing_mode = cuvis.ProcessingMode.SpectralRadiance\n", + "\n", + "# Set dark reference\n", + "processing_context.set_reference(dark_mesu, cuvis.ReferenceType.Dark)\n", + "\n", + "# Compute a cube in Spectral Radiance mode for the measurement\n", + "processing_context.apply(measurement)\n", + "# Show data\n", + "print_processing_mode(measurement)\n", + "show_spectrum_and_channel(measurement)" + ] + }, + { + "cell_type": "markdown", + "id": "fb8828fb-eb2f-4280-9d4c-a97ff19cf712", + "metadata": {}, + "source": [ + "#### Distance Calibration\n", + "Most Ultris cameras (except for Relay-variants) require distance calibration to achieve optimal results.\n", + "Distance calibration is an operation that can be done with already recorded data and requires a distance reference measurement.\n", + "The reference should contain high-contrast data over the relevant spectral channels at the desired distance that data should be calibrated to.\n", + "\n", + "In this example, the measurement itself will be used as the distance reference. If the target object is suitable (high contrast, non-repeating patterns), this can suffice for good results." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5924d2f-a6b3-44fb-9027-5cfcf93b7c37", + "metadata": {}, + "outputs": [], + "source": [ + "# Set processing mode\n", + "processing_context.processing_mode = cuvis.ProcessingMode.Reflectance\n", + "\n", + "# Set references\n", + "processing_context.set_reference(dark_mesu, cuvis.ReferenceType.Dark)\n", + "processing_context.set_reference(white_mesu, cuvis.ReferenceType.White)\n", + "processing_context.set_reference(measurement, cuvis.ReferenceType.Distance)\n", + "\n", + "# Compute a cube in Spectral Radiance mode for the measurement\n", + "processing_context.apply(measurement)\n", + "# Show data\n", + "print_processing_mode(measurement)\n", + "show_spectrum_and_channel(measurement)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From ef329e3eeee7970287536515b311db9f816d544b Mon Sep 17 00:00:00 2001 From: Philip Manke Date: Wed, 27 Aug 2025 17:01:34 +0200 Subject: [PATCH 02/11] Remove old examples; Add notebook for example 4 --- .gitignore | 1 + EX01_loadMeasurement.py | 89 ---- EX02_reprocessMeasurement.py | 142 ------- EX03_exportMeasurement.py | 107 ----- EX04_changeDistance.py | 95 ----- EX05_recordSingleImages.py | 117 ------ EX05_recordSingleImages_async.py | 116 ----- EX06_recordVideo.py | 170 -------- EX06_recordVideo_async.py | 166 -------- EX07_recordVideoFromSessionFile.py | 164 -------- EX08_pansharpenMeasurement.py | 135 ------ ...hot.ipynb => Example_1_Take_Snapshot.ipynb | 66 ++- ....ipynb => Example_2_Load_Measurement.ipynb | 19 +- ...process.ipynb => Example_3_Reprocess.ipynb | 53 ++- Example_4_Exporters.ipynb | 395 ++++++++++++++++++ README.md | 45 +- requirements.txt | 3 +- 17 files changed, 507 insertions(+), 1376 deletions(-) delete mode 100644 EX01_loadMeasurement.py delete mode 100644 EX02_reprocessMeasurement.py delete mode 100644 EX03_exportMeasurement.py delete mode 100644 EX04_changeDistance.py delete mode 100644 EX05_recordSingleImages.py delete mode 100644 EX05_recordSingleImages_async.py delete mode 100644 EX06_recordVideo.py delete mode 100644 EX06_recordVideo_async.py delete mode 100644 EX07_recordVideoFromSessionFile.py delete mode 100644 EX08_pansharpenMeasurement.py rename notebooks/Example_1_Take_Snapshot.ipynb => Example_1_Take_Snapshot.ipynb (69%) rename notebooks/Example_2_Load_Measurement.ipynb => Example_2_Load_Measurement.ipynb (92%) rename notebooks/Example_3_Reprocess.ipynb => Example_3_Reprocess.ipynb (86%) create mode 100644 Example_4_Exporters.ipynb diff --git a/.gitignore b/.gitignore index cace7ec..90633df 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ /.venv /.venv39 /exit +*.log \ No newline at end of file diff --git a/EX01_loadMeasurement.py b/EX01_loadMeasurement.py deleted file mode 100644 index b722ea4..0000000 --- a/EX01_loadMeasurement.py +++ /dev/null @@ -1,89 +0,0 @@ -import os -import platform -from pathlib import Path - -import matplotlib.pyplot as plt -import numpy as np - -import cuvis - - -def run_example_loadMeasurement( - userSettingsDir, - measurementLoc): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading session...") - session = cuvis.SessionFile(measurementLoc) - - print("loading measurement file...") - mesu = session[0] - assert mesu._handle - - print("Data 1 {} t={}ms mode={}".format(mesu.name, - mesu.integration_time, - mesu.processing_mode.name, - )) - - if isinstance(mesu.measurement_flags, cuvis.MeasurementFlags): - print(f"Flags: {mesu.measurement_flags}") - for v in cuvis.MeasurementFlags.supremum(): - print(f'{v}: {v in mesu.measurement_flags}') - - cube = mesu.cube - if cube is None: - raise Exception("Cube not found") - - x = 120 - y = 200 - - assert x < cube.width, "x index exceeds cube width!" - assert y < cube.height, "y index exceeds cube height!" - - lambda_wl = [] - raw_counts = [] - for chn in np.arange(cube.channels): - lambda_wl.append(cube.wavelength[chn]) - raw_counts.append(cube.array[x, y, chn]) - - plt.plot(lambda_wl, raw_counts) - plt.xlabel("lambda [nm]") - plt.ylabel("raw counts [au]") - plt.title("Spectrum of {} for x={}, y={}".format(mesu.name, x, y)) - plt.show() - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - data_dir = Path(os.getenv("CUVIS")).parent / "sdk" / \ - "sample_data" / "set_examples" - - elif platform.system() == "Linux": - data_dir = Path(os.getenv("CUVIS_DATA")) / \ - "sample_data" / "set_examples" - - # default image - loc_file = data_dir / "set0_single" / "single.cu3s" - - # default settings - loc_settings = data_dir / "settings" - - print("Example 01: Load Measurement. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - measurementLoc = input( - "Measurement file (.cu3s) (default: {}): ".format(loc_file)) - if measurementLoc.strip().lower() in ["", "default"]: - measurementLoc = loc_file - - run_example_loadMeasurement(str(userSettingsDir), str(measurementLoc)) diff --git a/EX02_reprocessMeasurement.py b/EX02_reprocessMeasurement.py deleted file mode 100644 index b1eb0a7..0000000 --- a/EX02_reprocessMeasurement.py +++ /dev/null @@ -1,142 +0,0 @@ -import os -import platform -from pathlib import Path - -import cuvis - - -def run_example_reprocessMeasurement( - userSettingsDir, - measurementLoc, - darkLoc, - whiteLoc, - distanceLoc, - outDir): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading measurement file...") - sessionM = cuvis.SessionFile(measurementLoc) - mesu = sessionM[0] - assert mesu._handle - - print("loading dark...") - sessionDk = cuvis.SessionFile(darkLoc) - dark = sessionDk[0] - assert dark._handle - - print("loading white...") - sessionWt = cuvis.SessionFile(whiteLoc) - white = sessionWt[0] - assert white._handle - - print("loading distance...") - sessionDc = cuvis.SessionFile(distanceLoc) - distance = sessionDc[0] - assert distance._handle - - print("Data 1 {} t={}ms mode={}".format(mesu.name, - mesu.integration_time, - mesu.processing_mode.name, - )) - - print("loading processing context...") - processingContext = cuvis.ProcessingContext(sessionM) - - print("set references...") - processingContext.set_reference(dark, cuvis.ReferenceType.Dark) - processingContext.set_reference(white, cuvis.ReferenceType.White) - processingContext.set_reference(distance, cuvis.ReferenceType.Distance) - - procArgs = cuvis.ProcessingArgs() - saveArgs = cuvis.SaveArgs(allow_overwrite=True, - allow_session_file=True, - allow_info_file=False) - - modes = [cuvis.ProcessingMode.Raw, - cuvis.ProcessingMode.DarkSubtract, - cuvis.ProcessingMode.Reflectance, - cuvis.ProcessingMode.SpectralRadiance - ] - - for mode in modes: - - procArgs.processing_mode = mode - - if processingContext.is_capable(mesu, procArgs): - print("processing to mode {}...".format(mode)) - processingContext.set_processing_args(procArgs) - mesu = processingContext.apply(mesu) - mesu.set_name(mode.name) - saveArgs.export_dir = str(Path(outDir) / mode.name) - exporter = cuvis.Export.CubeExporter(saveArgs) - exporter.apply(mesu) - - else: - print("Cannot process to {} mode!".format(mode)) - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - data_dir = Path(os.getenv("CUVIS")).parent / "sdk" / \ - "sample_data" / "set_examples" - - elif platform.system() == "Linux": - data_dir = Path(os.getenv("CUVIS_DATA")) / \ - "sample_data" / "set_examples" - - # default images - loc_file = data_dir / "set0_single" / "single_raw.cu3s" - loc_dark = data_dir / "set0_single" / "single_dark.cu3s" - loc_white = data_dir / "set0_single" / "single_white.cu3s" - - loc_distance = data_dir / "set0_single" / "single_distance.cu3s" - - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX02_reprocessed" - - print( - "Example 02: Reprocess Measurement. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - measurementLoc = input( - "Measurement file (.cu3s) (default: {}): ".format(loc_file)) - if measurementLoc.strip().lower() in ["", "default"]: - measurementLoc = loc_file - - darkLoc = input("Dark file (.cu3s) (default: {}): ".format(loc_dark)) - if darkLoc.strip().lower() in ["", "default"]: - darkLoc = loc_dark - - whiteLoc = input("White file (.cu3s) (default: {}): ".format(loc_white)) - if whiteLoc.strip().lower() in ["", "default"]: - whiteLoc = loc_white - - distanceLoc = input( - "Distance file (.cu3s) (default: {}): ".format(loc_distance)) - if distanceLoc.strip().lower() in ["", "default"]: - distanceLoc = loc_distance - - outDir = input( - "Name of output directory (default: {}): ".format(loc_output)) - if outDir.strip().lower() in ["", "default"]: - outDir = loc_output - - run_example_reprocessMeasurement(str(userSettingsDir), - str(measurementLoc), - str(darkLoc), - str(whiteLoc), - str(distanceLoc), - str(outDir)) diff --git a/EX03_exportMeasurement.py b/EX03_exportMeasurement.py deleted file mode 100644 index f31856d..0000000 --- a/EX03_exportMeasurement.py +++ /dev/null @@ -1,107 +0,0 @@ -import os -import platform -from pathlib import Path - -import cuvis - - -def run_example_exportMeasurement(userSettingsDir, - measurementLoc, - pluginLoc, - exportDir): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading session file...") - session = cuvis.SessionFile(measurementLoc) - mesu = session[0] - assert mesu._handle - - assert mesu.processing_mode != cuvis.ProcessingMode.Preview, "Wrong processing mode: {}".format( - mesu.processing_mode.name) - - print("Export to Envi...") - envi_settings = cuvis.EnviExportSettings( - export_dir=os.path.join(exportDir, "envi")) - enviExporter = cuvis.EnviExporter(envi_settings) - enviExporter.apply(mesu) - - print("Export to Multi-Channel Tiff...") - multi_tiff_settings = cuvis.TiffExportSettings( - export_dir=os.path.join(exportDir, "multi"), format=cuvis.TiffFormat.MultiChannel) - multiTiffExporter = cuvis.TiffExporter(multi_tiff_settings) - multiTiffExporter.apply(mesu) - - print("Export to separate Tiffs...") - single_tiff_settings = cuvis.TiffExportSettings( - export_dir=os.path.join(exportDir, "single"), format=cuvis.TiffFormat.Single) - singleTiffExporter = cuvis.TiffExporter(single_tiff_settings) - singleTiffExporter.apply(mesu) - - print("Export View to file...") - - print("load plugin...") - with open(pluginLoc) as f: - userpluginCai = f.readlines() - userpluginCai = "".join(userpluginCai) - - view_export_settings = cuvis.ViewExportSettings( - export_dir=os.path.join(exportDir, "view"), userplugin=userpluginCai) - # also view_export_settings = cuvis.ViewExportSettings(ExportDir=os.path.join(exportDir, "view"), - # Userplugin=pluginLoc) works! - viewExporter = cuvis.ViewExporter(view_export_settings) - viewExporter.apply(mesu) - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - plugin_dir = lib_dir.parent / "user" / "plugin" - - elif platform.system() == "Linux": - lib_dir = Path(os.getenv("CUVIS_DATA")) - data_dir = lib_dir / \ - "sample_data" / "set_examples" - plugin_dir = lib_dir / "user" / "plugin" - - # default images - loc_file = data_dir / "set0_single" / "single.cu3s" - loc_plugin = plugin_dir / "ref" / "cai.xml" - - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX03_export" - - print("Example 03: Export Measurement. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - measurementLoc = input( - "Measurement file (.cu3) (default: {}): ".format(loc_file)) - if measurementLoc.strip().lower() in ["", "default"]: - measurementLoc = loc_file - - pluginLoc = input( - "User plugin file (.xml) (default: {}): ".format(loc_plugin)) - if pluginLoc.strip().lower() in ["", "default"]: - pluginLoc = loc_plugin - - exportDir = input( - "Name of export directory (default: {}): ".format(loc_output)) - if exportDir.strip().lower() in ["", "default"]: - exportDir = loc_output - - run_example_exportMeasurement(str(userSettingsDir), str(measurementLoc), str(pluginLoc), - str(exportDir)) diff --git a/EX04_changeDistance.py b/EX04_changeDistance.py deleted file mode 100644 index 77b9ee9..0000000 --- a/EX04_changeDistance.py +++ /dev/null @@ -1,95 +0,0 @@ -import os -import platform -from pathlib import Path - -import cuvis - - -def run_example_changeDistance(userSettingsDir, - measurementLoc, - distance, - exportDir): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading session file...") - session = cuvis.SessionFile(measurementLoc) - mesu = session[0] - assert mesu._handle - - print("Data 1 {} t={}ms mode={}".format(mesu.name, - mesu.integration_time, - mesu.processing_mode.name, - )) - - print("loading calibration and processing context (factory)...") - processingContext = cuvis.ProcessingContext(session) - - print("setting distance...") - processingContext.calc_distance(distance) - - processingContext.processing_mode = cuvis.ProcessingMode.Raw - - saveArgs = cuvis.SaveArgs(export_dir=exportDir, allow_overwrite=True) - - assert processingContext.is_capable(mesu, - processingContext.get_processing_args()) - - print("changing distance...") - print("original distance...") - print(mesu.distance) - processingContext.apply(mesu) - print("new distance...") - print(mesu.distance) - print("saving...") - mesu.save(saveArgs) - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - data_dir = Path(os.getenv("CUVIS")).parent / "sdk" / \ - "sample_data" / "set_examples" - - elif platform.system() == "Linux": - data_dir = Path(os.getenv("CUVIS_DATA")) / \ - "sample_data" / "set_examples" - - # default image - loc_file = data_dir / "set0_single" / "single.cu3s" - # default settings - loc_settings = data_dir / "settings" - - loc_distance = int(1000) - - # default output - loc_output = Path(os.getcwd()) / "EX04_distance_changed" - - print("Example 04: Change distance. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - measurementLoc = input( - "Measurement file (.cu3) (default: {}): ".format(loc_file)) - if measurementLoc.strip().lower() in ["", "default"]: - measurementLoc = loc_file - - distance = input("New distance in mm (default: {}): ".format(loc_distance)) - if distance.strip().lower() in ["", "default"]: - distance = loc_distance - distance = int(distance) - - exportDir = input( - "Name of export directory (default: {}): ".format(loc_output)) - if exportDir.strip().lower() in ["", "default"]: - exportDir = loc_output - - run_example_changeDistance(str(userSettingsDir), str(measurementLoc), - distance, str(exportDir)) diff --git a/EX05_recordSingleImages.py b/EX05_recordSingleImages.py deleted file mode 100644 index c9fdfd1..0000000 --- a/EX05_recordSingleImages.py +++ /dev/null @@ -1,117 +0,0 @@ -import os -import platform -import time -from datetime import timedelta -from pathlib import Path - -import cuvis - - -def run_example_recordSingleImage( - userSettingsDir: str, - factoryDir: Path, - recDir: str, - exposure: int, - nrImgs: int): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print( - "loading calibration, processing and acquisition context (factory)...") - if (factoryDir.is_dir()): - calibration = cuvis.Calibration(factoryDir) - elif (factoryDir.suffix == '.cu3c'): - print("using .cu3c file as calibration instead of factory dir...") - calibFile = cuvis.SessionFile(factoryDir) - calibration = cuvis.Calibration(calibFile) - else: - raise ValueError('Unrecognized file format') - processingContext = cuvis.ProcessingContext(calibration) - acquisitionContext = cuvis.AcquisitionContext(calibration) - - saveArgs = cuvis.SaveArgs(export_dir=recDir, allow_overwrite=True, - allow_session_file=True) - cubeExporter = cuvis.CubeExporter(saveArgs) - - while acquisitionContext.state == cuvis.HardwareState.Offline: - print(".", end="") - time.sleep(1) - print("\n") - - print("Camera is online") - acquisitionContext.operation_mode = cuvis.OperationMode.Software - acquisitionContext.integration_time = exposure - - print("Start recoding now") - for i in range(nrImgs): - print("Record image #{}/{} ... (async)".format(i + 1, nrImgs)) - am = acquisitionContext.capture() - mesu, res = am.get(timedelta(milliseconds=500)) - if mesu is not None: - - processingContext.apply(mesu) - cubeExporter.apply(mesu) - - print("done") - - else: - print("failed") - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - elif platform.system() == "Linux": - lib_dir = os.getenv("CUVIS_DATA") - data_dir = lib_dir / \ - "sample_data" / "set_examples" - - # default factory - loc_factory = lib_dir.parent / "factory" - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX05_images" - - # parameters - loc_exptime = 100 # in msw - loc_nimgs = 10 - - print("Example 05: Record single image. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - factoryDir = input( - "Factory directory (default: {}) or .cu3c file: ".format(loc_factory)) - if factoryDir.strip().lower() in ["", "default"]: - factoryDir = loc_factory - - recDir = input( - "Name of recording directory (default: {}): ".format(loc_output)) - if recDir.strip().lower() in ["", "default"]: - recDir = loc_output - - exposure = input( - "Exposure/Integration time in ms (default: {}): ".format(loc_exptime)) - if exposure.strip().lower() in ["", "default"]: - exposure = loc_exptime - exposure = int(exposure) - - nrImgs = input("Number of Images (default: {}): ".format(loc_nimgs)) - if nrImgs.strip().lower() in ["", "default"]: - nrImgs = loc_nimgs - nrImgs = int(nrImgs) - - run_example_recordSingleImage(str(userSettingsDir), Path(factoryDir), str(recDir), exposure, - nrImgs) diff --git a/EX05_recordSingleImages_async.py b/EX05_recordSingleImages_async.py deleted file mode 100644 index 25786b4..0000000 --- a/EX05_recordSingleImages_async.py +++ /dev/null @@ -1,116 +0,0 @@ -import os -import platform -import time -from datetime import timedelta -from pathlib import Path - -import cuvis - -import asyncio as a - - -async def run_example_recordSingleImage( - userSettingsDir: str, - factoryDir: Path, - recDir: str, - exposure: int, - nrImgs: int): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print( - "loading calibration, processing and acquisition context (factory)...") - if (factoryDir.is_dir()): - calibration = cuvis.Calibration(factoryDir) - elif (factoryDir.suffix == '.cu3c'): - print("using .cu3c file as calibration instead of factory dir...") - calibFile = cuvis.SessionFile(factoryDir) - calibration = cuvis.Calibration(calibFile) - else: - raise ValueError('Unrecognized file format') - processingContext = cuvis.ProcessingContext(calibration) - acquisitionContext = cuvis.AcquisitionContext(calibration) - - saveArgs = cuvis.SaveArgs(export_dir=recDir, allow_overwrite=True, - allow_session_file=True) - cubeExporter = cuvis.CubeExporter(saveArgs) - - while acquisitionContext.state == cuvis.HardwareState.Offline: - print(".", end="") - time.sleep(1) - print("\n") - - print("Camera is online") - await acquisitionContext.set_operation_mode_async(cuvis.OperationMode.Software) - await acquisitionContext.set_integration_time_async(exposure) - - print("Start recoding now") - for i in range(nrImgs): - print("Record image #{}/{} ... (async)".format(i + 1, nrImgs)) - mesu = await acquisitionContext.capture() - if mesu is not None: - processingContext.apply(mesu) - cubeExporter.apply(mesu) - - print("done") - else: - print("failed") - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - elif platform.system() == "Linux": - lib_dir = os.getenv("CUVIS_DATA") - data_dir = lib_dir / \ - "sample_data" / "set_examples" - - # default factory - loc_factory = lib_dir.parent / "factory" - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX05_images" - - # parameters - loc_exptime = 100 # in msw - loc_nimgs = 10 - - print("Example 05: Record single image. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - factoryDir = input( - "Factory directory (default: {}) or .cu3c file: ".format(loc_factory)) - if factoryDir.strip().lower() in ["", "default"]: - factoryDir = loc_factory - - recDir = input( - "Name of recording directory (default: {}): ".format(loc_output)) - if recDir.strip().lower() in ["", "default"]: - recDir = loc_output - - exposure = input( - "Exposure/Integration time in ms (default: {}): ".format(loc_exptime)) - if exposure.strip().lower() in ["", "default"]: - exposure = loc_exptime - exposure = int(exposure) - - nrImgs = input("Number of Images (default: {}): ".format(loc_nimgs)) - if nrImgs.strip().lower() in ["", "default"]: - nrImgs = loc_nimgs - nrImgs = int(nrImgs) - - a.run(run_example_recordSingleImage(str(userSettingsDir), Path(factoryDir), str(recDir), exposure, - nrImgs)) diff --git a/EX06_recordVideo.py b/EX06_recordVideo.py deleted file mode 100644 index 1a84390..0000000 --- a/EX06_recordVideo.py +++ /dev/null @@ -1,170 +0,0 @@ -import os -import platform -import time -from datetime import datetime, timedelta -from pathlib import Path - -import cuvis - - -def run_example_recordVideo(userSettingsDir: str, - factoryDir: Path, - recDir: str, - exposure: int, - autoExp: bool, - fps: float): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading calibration (factory)...") - if (factoryDir.is_dir()): - calibration = cuvis.Calibration(factoryDir) - elif (factoryDir.suffix == '.cu3c'): - print("using .cu3c file as calibration instead of factory dir...") - calibFile = cuvis.SessionFile(factoryDir) - calibration = cuvis.Calibration(calibFile) - else: - raise ValueError('Unrecognized file format') - - print("loading acquisition context...") - acquisitionContext = cuvis.AcquisitionContext(calibration) - session_info = cuvis.SessionData("video", 0, 0) - acquisitionContext.session_info = session_info - - print("prepare saving of measurements...") - saveArgs = cuvis.SaveArgs(export_dir=recDir, - allow_overwrite=True, - allow_session_file=True, - fps=fps, - operation_mode=cuvis.OperationMode.Software) - - print("writing files to: {}".format(recDir)) - cubeExporter = cuvis.CubeExporter(saveArgs) - - print("prepare processing of measurements...") - processingContext = cuvis.ProcessingContext(calibration) - processingContext.processing_mode = cuvis.ProcessingMode.Raw - - print("Waiting for camera to come online...") - - while acquisitionContext.state == cuvis.HardwareState.Offline: - print(".", end="") - time.sleep(1) - print("\n") - - print("Component details:") - for i, comp in enumerate(acquisitionContext.components()): - print("Component #{} {} is {}".format(i, comp.info.display_name, - "online" if comp.online else "offline")) - print(" -- info: {}".format(comp.info.sensor_info)) - print(" -- use: {}".format(comp.info.user_field)) - print(" -- pixelformat: {}".format(comp.info.pixel_format)) - - print("initializing hardware...") - acquisitionContext.integration_time = exposure - acquisitionContext.operation_mode = cuvis.OperationMode.Internal - acquisitionContext.fps = fps - acquisitionContext.auto_exp = autoExp - acquisitionContext.set_continuous(True) - - print("configuring worker...") - workerSettings = cuvis.WorkerSettings() - worker = cuvis.Worker(workerSettings) - worker.set_acquisition_context(acquisitionContext) - worker.set_processing_context(processingContext) - worker.set_exporter(cubeExporter) - worker.start_processing() - - print("recording...! (will stop after 2 minutes)") - start = datetime.now() - while (datetime.now() - start) < timedelta(minutes=2): - - while 1: - if worker.has_next_result(): - break - else: - time.sleep(0.001) - - workerContainer = worker.get_next_result(1000) # in ms - if workerContainer.mesu.data is not None: - print("current handle index: {}".format( - workerContainer.mesu.session_info.sequence_number)) - - workerState = worker.state - if workerState.resultsInQueue == worker.output_queue_limit: - print("worker output queue is full! Main() loop can not keep up!") - break - - if workerState.measurementsInQueue == worker.mandatory_queue_limit: - print("acquisition queue is full! Worker can not keep up!") - break - - print("acquisition stopped...") - acquisitionContext.set_continuous(False) - worker.stop_processing() - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - elif platform.system() == "Linux": - lib_dir = os.getenv("CUVIS_DATA") - data_dir = lib_dir / \ - "sample_data" / "set_examples" - - # default factory - loc_factory = lib_dir.parent / "factory" - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX06_video" - - # parameters - loc_exptime = 100 # in ms - loc_autoexp = False - loc_fps = 2 - - print("Example 06: Record video file. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - factoryDir = input( - "Factory directory (default: {}) or .cu3c file: ".format(loc_factory)) - if factoryDir.strip().lower() in ["", "default"]: - factoryDir = loc_factory - - recDir = input( - "Name of recording directory (default: {}): ".format(loc_output)) - if recDir.strip().lower() in ["", "default"]: - recDir = loc_output - - exposure = input( - "Exposure/Integration time in ms (default: {}): ".format(loc_exptime)) - if exposure.strip().lower() in ["", "default"]: - exposure = loc_exptime - exposure = int(exposure) - - autoExp = input( - "Auto-exposure time [True/False] (default: {}): ".format(loc_autoexp)) - if autoExp.strip().lower() in ["", "default"]: - autoExp = loc_autoexp - autoExp = int(autoExp) - - fps = input( - "Target frames per second (fps) (default: {}): ".format(loc_fps)) - if fps.strip().lower() in ["", "default"]: - fps = loc_fps - fps = float(fps) - - run_example_recordVideo(str(userSettingsDir), Path(factoryDir), str(recDir), exposure, - autoExp, fps) diff --git a/EX06_recordVideo_async.py b/EX06_recordVideo_async.py deleted file mode 100644 index 5da3399..0000000 --- a/EX06_recordVideo_async.py +++ /dev/null @@ -1,166 +0,0 @@ -import os -import platform -import time -from datetime import datetime, timedelta -import asyncio as a -from pathlib import Path - -import cuvis - - -async def state_changed_callback(state, component_states): - print(f'camera is {state.name}') - - -async def worker_collect_mesu_task(workerContainer: cuvis.WorkerResult): - if workerContainer.mesu.data is not None: - print("current handle index: {}".format( - workerContainer.mesu.session_info.sequence_number)) - - -async def run_example_recordVideo(userSettingsDir: str, - factoryDir: Path, - recDir: str, - exposure: int, - autoExp: bool, - fps: float): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading calibration (factory)...") - if (factoryDir.is_dir()): - calibration = cuvis.Calibration(factoryDir) - elif (factoryDir.suffix == '.cu3c'): - print("using .cu3c file as calibration instead of factory dir...") - calibFile = cuvis.SessionFile(factoryDir) - calibration = cuvis.Calibration(calibFile) - else: - raise ValueError('Unrecognized file format') - - print("loading acquisition context...") - acquisitionContext = cuvis.AcquisitionContext(calibration) - session_info = cuvis.SessionData('video', 0, 0) - acquisitionContext.session_info = session_info - - print("prepare saving of measurements...") - saveArgs = cuvis.SaveArgs(export_dir=recDir, - allow_overwrite=True, - allow_session_file=True, - fps=fps, - operation_mode=cuvis.OperationMode.Software) - - print("writing files to: {}".format(recDir)) - cubeExporter = cuvis.CubeExporter(saveArgs) - - print("prepare processing of measurements...") - processingContext = cuvis.ProcessingContext(calibration) - processingContext.processing_mode = cuvis.ProcessingMode.Raw - - acquisitionContext.register_state_change_callback(state_changed_callback) - - print("Waiting for camera to come online...") - - while acquisitionContext.state == cuvis.HardwareState.Offline: - print(".", end="") - await a.sleep(1) - print("\n") - - print("Component details:") - for i, comp in enumerate(acquisitionContext.components()): - print("Component #{} {} is {}".format(i, comp.info.display_name, - "online" if comp.online else "offline")) - print(" -- info: {}".format(comp.info.sensor_info)) - print(" -- use: {}".format(comp.info.user_field)) - print(" -- pixelformat: {}".format(comp.info.pixel_format)) - - print("initializing hardware...") - await acquisitionContext.set_integration_time_async(exposure) - await acquisitionContext.set_operation_mode_async(cuvis.OperationMode.Internal) - await acquisitionContext.set_fps_async(fps) - await acquisitionContext.set_auto_exp_async(autoExp) - await acquisitionContext.set_continuous_async(True) - - print("configuring worker...") - workerSettings = cuvis.WorkerSettings() - worker = cuvis.Worker(workerSettings) - worker.set_acquisition_context(acquisitionContext) - worker.set_processing_context(processingContext) - worker.set_exporter(cubeExporter) - - print("recording...! (will stop after 2 minutes)") - - worker.register_worker_callback(worker_collect_mesu_task) - worker.start_processing() - - await a.sleep(2 * 60) - worker.reset_worker_callback() - - print("acquisition stopped...") - await acquisitionContext.set_continuous_async(False) - worker.stop_processing() - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - elif platform.system() == "Linux": - lib_dir = os.getenv("CUVIS_DATA") - data_dir = lib_dir / \ - "sample_data" / "set_examples" - - # default factory - loc_factory = lib_dir.parent / "factory" - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX06_video" - - # parameters - loc_exptime = 100 # in ms - loc_autoexp = False - loc_fps = 2 - - print("Example 06: Record video file. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - factoryDir = input( - "Factory directory (default: {}) or .cu3c file: ".format(loc_factory)) - if factoryDir.strip().lower() in ["", "default"]: - factoryDir = loc_factory - - recDir = input( - "Name of recording directory (default: {}): ".format(loc_output)) - if recDir.strip().lower() in ["", "default"]: - recDir = loc_output - - exposure = input( - "Exposure/Integration time in ms (default: {}): ".format(loc_exptime)) - if exposure.strip().lower() in ["", "default"]: - exposure = loc_exptime - exposure = int(exposure) - - autoExp = input( - "Auto-exposure time [True/False] (default: {}): ".format(loc_autoexp)) - if autoExp.strip().lower() in ["", "default"]: - autoExp = loc_autoexp - autoExp = int(autoExp) - - fps = input( - "Target frames per second (fps) (default: {}): ".format(loc_fps)) - if fps.strip().lower() in ["", "default"]: - fps = loc_fps - fps = float(fps) - - a.run(run_example_recordVideo(str(userSettingsDir), Path(factoryDir), str(recDir), exposure, - autoExp, fps)) diff --git a/EX07_recordVideoFromSessionFile.py b/EX07_recordVideoFromSessionFile.py deleted file mode 100644 index ade2a86..0000000 --- a/EX07_recordVideoFromSessionFile.py +++ /dev/null @@ -1,164 +0,0 @@ -import os -import platform -import time -from datetime import datetime, timedelta -from pathlib import Path - -import cuvis - - -def run_example_recordVideoFromSessionFile(userSettingsDir, - measurementLoc, - recDir, - exposure, - autoExp, - fps): - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading session file ...") - session = cuvis.SessionFile(measurementLoc) - - print("loading acquisition context...") - acquisitionContext = cuvis.AcquisitionContext(session, simulate=True) # - # using images from session file instead of camera - session_info = cuvis.SessionData("video", 0, 0) - acquisitionContext.session_info = session_info - - print("prepare saving of measurements...") - saveArgs = cuvis.SaveArgs(export_dir=recDir, - allow_overwrite=True, - allow_session_file=True, - fps=fps, - operation_mode=cuvis.OperationMode.Internal) - - print("writing files to: {}".format(recDir)) - cubeExporter = cuvis.CubeExporter(saveArgs) - - print("prepare processing of measurements...") - processingContext = cuvis.ProcessingContext(session) - processingContext.processing_mode = cuvis.ProcessingMode.Raw - - print("Waiting for camera to come online...") - - while acquisitionContext.state == cuvis.HardwareState.Offline: - print(".", end="") - time.sleep(1) - print("\n") - - print("Component details:") - print("Component details:") - for i, (info, is_online) in enumerate(acquisitionContext.components()): - print("Component #{} {} is {}".format(i, info.display_name, - "online" if is_online else "offline")) - print(" -- info: {}".format(info.sensor_info)) - print(" -- use: {}".format(info.user_field)) - print(" -- pixelformat: {}".format(info.pixel_format)) - - print("initializing simulated hardware...") - acquisitionContext.integration_time = exposure - acquisitionContext.operation_mode = cuvis.OperationMode.Internal - acquisitionContext.fps = fps - acquisitionContext.auto_exp = autoExp - acquisitionContext.set_continuous(True) - - print("configuring worker...") - workerSettings = cuvis.WorkerSettings() - worker = cuvis.Worker(workerSettings) - worker.set_acquisition_context(acquisitionContext) - worker.set_processing_context(processingContext) - worker.set_exporter(cubeExporter) - worker.start_processing() - - print("recording...! (will stop after 2 minutes)") - start = datetime.now() - while (datetime.now() - start) < timedelta(minutes=2): - - while 1: - if worker.has_next_result(): - break - else: - time.sleep(0.001) - - workerContainer = worker.get_next_result(0) - if workerContainer.mesu.data is not None: - print("current handle index: {}".format( - workerContainer.mesu.session_info.sequence_number)) - - workerState = worker.state - if workerState.resultsInQueue == worker.output_queue_limit: - print("worker output queue is full! Main() loop can not keep up!") - break - - if workerState.measurementsInQueue == worker.mandatory_queue_limit: - print("acquisition queue is full! Worker can not keep up!") - break - - print("acquisition stopped...") - acquisitionContext.set_continuous(False) - worker.stop_processing() - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - lib_dir = Path(os.getenv("CUVIS")) - data_dir = lib_dir.parent / "sdk" / \ - "sample_data" / "set_examples" - elif platform.system() == "Linux": - lib_dir = os.getenv("CUVIS_DATA") - data_dir = lib_dir / \ - "sample_data" / "set_examples" - - # default video - loc_file = data_dir / "set1_video" / "video.cu3s" - # default settings - loc_settings = data_dir / "settings" - - # default output - loc_output = Path(os.getcwd()) / "EX07_video" - - # parameters - loc_exptime = 100 # in ms - loc_autoexp = False - loc_fps = 2 - - print("Example 07: Record video from session file. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - factoryDir = input("Session file (default: {}): ".format( - loc_file)) - if factoryDir.strip().lower() in ["", "default"]: - factoryDir = loc_file - - recDir = input( - "Name of recording directory (default: {}): ".format(loc_output)) - if recDir.strip().lower() in ["", "default"]: - recDir = loc_output - - exposure = input( - "Exposure/Integration time in ms (default: {}): ".format(loc_exptime)) - if exposure.strip().lower() in ["", "default"]: - exposure = loc_exptime - exposure = int(exposure) - - autoExp = input( - "Auto-exposure time [True/False] (default: {}): ".format(loc_autoexp)) - if autoExp.strip().lower() in ["", "default"]: - autoExp = loc_autoexp - - fps = input( - "Target frames per second (fps) (default: {}): ".format(loc_fps)) - if fps.strip().lower() in ["", "default"]: - fps = loc_fps - fps = int(fps) - - run_example_recordVideoFromSessionFile(str(userSettingsDir), str(factoryDir), str(recDir), exposure, - autoExp, fps) diff --git a/EX08_pansharpenMeasurement.py b/EX08_pansharpenMeasurement.py deleted file mode 100644 index 6e386f0..0000000 --- a/EX08_pansharpenMeasurement.py +++ /dev/null @@ -1,135 +0,0 @@ -import os -import platform -from pathlib import Path -import time - -import cuvis -import tifffile - -def run_example_pansharpening(userSettingsDir, - measurementLoc, - panToCube, - panScale, - exportDir): - - print("loading user settings...") - cuvis.init(userSettingsDir) - cuvis.set_log_level("info") - - print("loading session file...") - session = cuvis.SessionFile(measurementLoc) - mesu = session[0] - assert mesu._handle - - if 'pan' not in mesu.data.keys(): - raise ValueError('The measurement does not contain a Pan Image.') - - # settings pansharpening - ''' - cuvis.PansharpeningAlgorithm: - Defines, which algorithm is used to calculate the pansharpened image. Available options are: - - Noop: - "dummy" algorithm, only applies scaling. - - CubertMacroPixel: - Generates intensity scaling values for the spectral data from the panimage. Can operate without - reference measurements. - - CubertPanRatio: - Preferred algorithm for reflectance measurements. The measurement's and white calibration's panimages - are used to generate the panratio (or „panchromatic reflectance“ image). The panratio is then applied - to the hyperspectral cube to scale the intensity of the spectra without changing their shape. - - AlphaBlendOverlay: - Technically not a pan-sharpening algorithm. Quick workaround to display correlation results on top of - the pan image using an opacity value selected by the user. - ''' - panAlgo = cuvis.PanSharpeningAlgorithm.CubertPanRatio # algorithm for pansharpening - - ''' - cuvis.PanSharpeningInterpolationType: - This setting controls which conventional algorithm is utilized for upscaling the hyperspectral data cube. - Available options are: Nearest Neighbor, Linear, Cubic and Lanczos - ''' - panInterp = cuvis.PanSharpeningInterpolationType.Cubic # interpolation method - - multi_tiff_settings = cuvis.TiffExportSettings( - export_dir = str(exportDir), - format = cuvis.TiffFormat.MultiChannel, - pan_sharpening_algorithm = panAlgo, - pan_sharpening_interpolation_type = panInterp, - pan_scale = panScale, - add_pan = panToCube - ) - - print("size before pansharpening: ", mesu.cube.width, "x", mesu.cube.height, "x", mesu.cube.channels) - print("Pansharpening and tiff export in progress...") - - multiTiffExporter = cuvis.TiffExporter(multi_tiff_settings) - multiTiffExporter.apply(mesu) - - time.sleep(5) - - exportPath= Path(exportDir) / "x20p_flight_data_0000_raw.tiff" - pansharpened_mesu = tifffile.imread(str(exportPath)) - - print("size after pansharpening: ", pansharpened_mesu.shape[0], "x", pansharpened_mesu.shape[1], "x", pansharpened_mesu.shape[2] ) - print("algorithm used:", str(panAlgo).split('.')[-1]) - print("Interpolation method used:", str(panInterp).split('.')[-1]) - print("Pansharpening amount:", panScale) - print("Panimage saved as 0th channel:", panToCube) - - cuvis.shutdown() - print("finished.") - - -if __name__ == "__main__": - - if platform.system() == "Windows": - data_dir = Path(os.getenv("CUVIS")).parent / "sdk" / \ - "sample_data" / "set_examples" - - elif platform.system() == "Linux": - data_dir = Path(os.getenv("CUVIS_DATA")) / \ - "sample_data" / "set_examples" - - loc_file = data_dir / "set2_x20p_flight_data" / "x20p_flight_data.cu3s" - loc_settings = data_dir / "settings" - - pan_to_cube = True - pan_size = 1 - - loc_output = Path(os.getcwd()) / "EX08_pansharpened_measurement" - - print("Example 08: Pansharpen X20 Plus measurement. Please provide:") - - userSettingsDir = input( - "User settings directory (default: {}): ".format(loc_settings)) - if userSettingsDir.strip().lower() in ["", "default"]: - userSettingsDir = loc_settings - - measurementLoc = input( - "Measurement file (.cu3s) (default: {}): ".format(loc_file)) - if measurementLoc.strip().lower() in ["", "default"]: - measurementLoc = loc_file - - panToCube = input( - "Save panimage as 0th channel - True/False? (default: {}): ".format(pan_to_cube)) - if panToCube.lower() in ["", "default"]: - panToCube = pan_to_cube # use the default boolean value - elif panToCube.lower() == "true": - panToCube = True - elif panToCube.lower() == "false": - panToCube = False - else: - raise ValueError("Invalid input. Please enter True or False.") - - panScale = input( - "Define the amount of pansharpening between 0 and 1 in respect to the size of the panimage (default: {}): ".format(pan_size)) - if panScale.strip().lower() in ["", "default"]: - panScale = pan_size - - exportDir = input( - "Name of export directory (default: {}): ".format(loc_output)) - if exportDir.strip().lower() in ["", "default"]: - exportDir = loc_output - - - run_example_pansharpening(str(userSettingsDir), str(measurementLoc), panToCube, panScale, exportDir) \ No newline at end of file diff --git a/notebooks/Example_1_Take_Snapshot.ipynb b/Example_1_Take_Snapshot.ipynb similarity index 69% rename from notebooks/Example_1_Take_Snapshot.ipynb rename to Example_1_Take_Snapshot.ipynb index 9fc5582..83cdd18 100644 --- a/notebooks/Example_1_Take_Snapshot.ipynb +++ b/Example_1_Take_Snapshot.ipynb @@ -23,10 +23,10 @@ " 5. Save the measurement to disk using the *CubeExporter*\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a camera connected\n", - " - Have the camera calibration file (*SN*.cu3c) ready\n", + " - Have a camera connected *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have the camera calibration file (*SN*.cu3c) ready *or* use the [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", " - Have the Cuvis SDK installed\n", - " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + " - Have Python and the requirements.txt installed" ] }, { @@ -61,8 +61,11 @@ "# Snapshot setup / User input\n", "# Enter your data here!\n", "snapshot_integration_time_ms = 100\n", - "save_directory = \"./data\"\n", - "camera_serial_number_str = \"ASR5232501\"\n", + "save_directory = \"./directory to save the measurements to here\"\n", + "camera_serial_number_str = \"Your camera serial here\"\n", + "\n", + "# If using demo data instead of a physical camera, change this to your download location:\n", + "demo_session_file = \"Your download location here /Lentils_2.0_XMR/Lentils_000.cu3s\"\n", "\n", "camera_calibration_file_path = F\"./factory/{camera_serial_number_str}.cu3c\"" ] @@ -73,6 +76,7 @@ "metadata": {}, "source": [ "#### Calibration Files (.cu3c)\n", + "This calibration file contains everything needed to connect to and process data from your camera.\n", "The **.cu3c** camera calibration file format is a special form of the SessionFile format **.cu3s**\n", "\n", "It is thus used as a calibration file and usually contains (among other things):\n", @@ -89,6 +93,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Skip this if working without a physical camera\n", "print(\"Load camera calibration file\")\n", "calib = cuvis.SessionFile(camera_calibration_file_path)" ] @@ -144,6 +149,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Skip this if working without a physical camera\n", "print(\"Loading Acquisition Context\")\n", "acq = cuvis.AcquisitionContext(calib)\n", "\n", @@ -159,6 +165,54 @@ "acq.integration_time = snapshot_integration_time" ] }, + { + "cell_type": "markdown", + "id": "3587f5af-9e8b-4e4a-853c-669f95469446", + "metadata": {}, + "source": [ + "#### Simulated Acquisition - great for testing without a camera\n", + "The *Acquisition Context* can be initialized with the **simulated** kwarg set to **True** to pretend it has a camera connected.\n", + "In this mode, it will provide the measurements from a *SessionFile* as if they where received from a physically connected camera.\n", + "Upon reaching the end of the file, it will loop back to the first measurement.\n", + "\n", + "With this simulated camera, you can record and test your code as if a physical camera was connected.\n", + "Some methods/attributes don't have any effect, as they cannot relay changes to a camera, eg. integration time, auto-exposure, gain, etc." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4080c54c-6341-4257-bbd4-d555372d8798", + "metadata": {}, + "outputs": [], + "source": [ + "# Simulated Acquisition: Skip this if working with a physical camera\n", + "session = cuvis.SessionFile(demo_session_file)\n", + "# Initialize the Acquisition Context in simulated camera mode\n", + "acq = cuvis.AcquisitionContext(session, simulate=True)\n", + "\n", + "# Wait for the Acquisition Context to load the demo session file\n", + "print(\"Wait for Acqusition Context to be ready...\")\n", + "while(not acq.ready):\n", + " time.sleep(1)\n", + " print(\".\", end=\"\")\n", + "print(\"\\nSimulated camera loaded!\")\n", + "\n", + "# Set simulated camera to software trigger\n", + "acq.operation_mode = cuvis.OperationMode.Software" + ] + }, + { + "cell_type": "markdown", + "id": "05924e40-63d1-40fb-9d7f-6c1253cae974", + "metadata": {}, + "source": [ + "#### Capturing a Measurement with Software Trigger (Single Snapshot)\n", + "Using the *capture()* method, a single measurement is initiated.\n", + "Taking a snapshot requires some time, so, to prevent the call to *capture()* from blocking execution, an *AsyncMesu* is returned.\n", + "To await the completion of the snapshot, use the *get()* method on the *AsyncMesu*. " + ] + }, { "cell_type": "code", "execution_count": null, @@ -185,7 +239,7 @@ "metadata": {}, "outputs": [], "source": [ - "# Export the measurement\n", + "# Export the measurement - write the data to the disk in SessionFile format using the CubeExporter\n", "if status == cuvis.Async.AsyncResult.done:\n", " exporter.apply(mesu)\n", " print(\"Measurement exported!\")\n", diff --git a/notebooks/Example_2_Load_Measurement.ipynb b/Example_2_Load_Measurement.ipynb similarity index 92% rename from notebooks/Example_2_Load_Measurement.ipynb rename to Example_2_Load_Measurement.ipynb index 8c52488..e3baefa 100644 --- a/notebooks/Example_2_Load_Measurement.ipynb +++ b/Example_2_Load_Measurement.ipynb @@ -23,9 +23,9 @@ " 5. Access data and meta-data from a single *Measurement*\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a recorded measurement in *SessionFile* format (.cu3s)\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", " - Have the Cuvis SDK installed\n", - " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + " - Have Python and the requirements.txt installed" ] }, { @@ -169,11 +169,11 @@ "# Each sensors meta-data is the sensor name + \"_info\" suffix.\n", "# You can iterate over the measurements data attribute to see all available data fields\n", "sensor_data = measurement.data[\"IMAGE_info\"]\n", - "print(F\"Sensor pixel format: {camera_data.pixel_format}\")\n", - "print(F\"Sensor readout timestamp: {camera_data.readout_time}\")\n", - "print(F\"Sensor gain value: {camera_data.gain}\")\n", - "print(F\"Raw sensor size (WxH): ({camera_data.width}, {camera_data.height}) pixel\")\n", - "print(F\"Sensor temperature: {camera_data.temperature} °C\")" + "print(F\"Sensor pixel format: {sensor_data.pixel_format}\")\n", + "print(F\"Sensor readout timestamp: {sensor_data.readout_time}\")\n", + "print(F\"Sensor gain value: {sensor_data.gain}\")\n", + "print(F\"Raw sensor size (WxH): ({sensor_data.width}, {sensor_data.height}) pixel\")\n", + "print(F\"Sensor temperature: {sensor_data.temperature} °C\")" ] }, { @@ -185,8 +185,9 @@ "source": [ "# Access the hyperspectral cube\n", "\n", - "# If the cube is not generated, compute it now\n", - "# The Processing Context is explained in detail in example 3\n", + "# If the cube is not generated, compute it now!\n", + "# By default, SessionFiles are saved without the cube to save disk space \n", + "# -> The Processing Context is explained in detail in example 3 <-\n", "if measurement.processing_mode == cuvis.ProcessingMode.Preview:\n", " pc = cuvis.ProcessingContext(session)\n", " pc.processing_mode = cuvis.ProcessingMode.Raw\n", diff --git a/notebooks/Example_3_Reprocess.ipynb b/Example_3_Reprocess.ipynb similarity index 86% rename from notebooks/Example_3_Reprocess.ipynb rename to Example_3_Reprocess.ipynb index b690338..7639ba6 100644 --- a/notebooks/Example_3_Reprocess.ipynb +++ b/Example_3_Reprocess.ipynb @@ -24,10 +24,10 @@ " 5. Use *ProcessingContext* to generate hyperspectral cubes\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a recorded measurement in *SessionFile* format (.cu3s)\n", - " - Have a recorded White and Dark reference measurement\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have a recorded White and Dark reference measurement *or* use the [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", " - Have the Cuvis SDK installed\n", - " - Have Python and the and the Python packages **cuvis** and **notebook** installed" + " - Have Python and the requirements.txt installed" ] }, { @@ -62,9 +62,9 @@ "outputs": [], "source": [ "# Enter paths applicable to your setup here\n", - "session_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", - "dark_reference_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", - "white_reference_file_path = \"D:/TestMesus/Blumen_NOPAN/Auto_001.cu3s\"\n", + "session_file_path = \"path/to/measurement.cu3s\"\n", + "dark_reference_file_path = \"path/to/reference measurement.cu3s\"\n", + "white_reference_file_path = \"path/to/reference measurement.cu3s\"\n", "\n", "# Load the SessionFile\n", "print(F\"Loading Session File '{session_file_path}'\")\n", @@ -116,11 +116,11 @@ " else:\n", " print(\"Unknown processing mode\")\n", "\n", - "def show_spectrum_and_channel(measurement):\n", + "def show_spectrum_and_channel(measurement, i_x=None, i_y=None, i_c=None):\n", " cube = measurement.cube\n", - " x = cube.width // 2\n", - " y = cube.height // 2\n", - " c = cube.channels // 2\n", + " x = (cube.width // 2) if i_x is None else i_x\n", + " y = (cube.height // 2) if i_y is None else i_y\n", + " c = (cube.channels // 2) if i_c is None else i_c\n", "\n", " procmode = measurement.processing_mode\n", " if procmode == cuvis.ProcessingMode.Preview:\n", @@ -223,7 +223,10 @@ "processing_context.apply(measurement)\n", "# Show data\n", "print_processing_mode(measurement)\n", - "show_spectrum_and_channel(measurement)" + "# By default shows spectrum of center pixel and channel of center wavelength\n", + "show_spectrum_and_channel(measurement) \n", + "# Show custom pixel and channel like this: e.g. pixel at (20, 100) and channel 10\n", + "#show_spectrum_and_channel(measurement, i_x=20, i_y=100, i_c=10)" ] }, { @@ -342,6 +345,9 @@ "source": [ "#### Distance Calibration\n", "Most Ultris cameras (except for Relay-variants) require distance calibration to achieve optimal results.\n", + "\n", + "**Please note:** The provided default demo dataset was recorded with a relay-equipped camera (Ultris XM with relay optics). Thus this step is not applicable to this dataset.\n", + "\n", "Distance calibration is an operation that can be done with already recorded data and requires a distance reference measurement.\n", "The reference should contain high-contrast data over the relevant spectral channels at the desired distance that data should be calibrated to.\n", "\n", @@ -361,13 +367,30 @@ "# Set references\n", "processing_context.set_reference(dark_mesu, cuvis.ReferenceType.Dark)\n", "processing_context.set_reference(white_mesu, cuvis.ReferenceType.White)\n", - "processing_context.set_reference(measurement, cuvis.ReferenceType.Distance)\n", + "processing_context.clear_reference(cuvis.ReferenceType.Distance)\n", "\n", - "# Compute a cube in Spectral Radiance mode for the measurement\n", + "# Compute a cube in Reflectance mode for the measurement\n", "processing_context.apply(measurement)\n", + "\n", "# Show data\n", - "print_processing_mode(measurement)\n", - "show_spectrum_and_channel(measurement)" + "# Note: The Viewer will be explained in detail in Example 5\n", + "# It is used here to generate an RGB view of the measurement as\n", + "# the effect of Distance calibration is not visible by only observing a single channel\n", + "viewer = cuvis.Viewer(cuvis.ViewerSettings(userplugin=\"Your Cuvis Install Dir here\" + \"/user/plugin/ref/00_RGB.xml\"))\n", + "view_nodistance = viewer.apply(measurement)\n", + "\n", + "# Set distance reference\n", + "processing_context.set_reference(measurement, cuvis.ReferenceType.Distance)\n", + "\n", + "# Compute a cube in Reflectance mode for the measurement with applied distance\n", + "processing_context.apply(measurement)\n", + "view_withdistance = viewer.apply(measurement)\n", + "\n", + "fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n", + "ax0.imshow(view_nodistance.array)\n", + "ax0.set_title(\"No Distance\")\n", + "ax1.imshow(view_withdistance.array)\n", + "ax1.set_title(\"With Distance\")" ] } ], diff --git a/Example_4_Exporters.ipynb b/Example_4_Exporters.ipynb new file mode 100644 index 0000000..b3ad369 --- /dev/null +++ b/Example_4_Exporters.ipynb @@ -0,0 +1,395 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "09ef3987-f280-4d53-b770-997a5a15913d", + "metadata": {}, + "source": [ + "# Cuvis Python SDK Example 4\n", + "## Export / Convert Cubert Measurements to Different File Formats\n", + "\n", + "This example provides information on the exporter classes and the file formats which they can convert measurements to.\n", + "\n", + "**Used principles:**\n", + " - *SessionFile* as a source for measurements\n", + " - *CubeExporter* for saving measurements\n", + " - *TiffExporter* for exporting to TIFF format\n", + " - *EnviExporter* for exporting to ENVI format\n", + " - *ViewExporter* for exporting rendered views of the data\n", + " - *UserPlugins* to define how a view is computed\n", + "\n", + "**Step-by-Step overview for this example:**\n", + " 1. Load measurements from a *SessionFile*\n", + " 2. Re-export as a *SessionFile* with different settings\n", + " 3. Export to TIFF\n", + " 4. Export to ENVI\n", + " 5. Load a *UserPlugin*\n", + " 6. Export a rendered view of a measurement as described by a *UserPlugin*\n", + "\n", + "**Prerequisites to running this example:**\n", + " - Have recorded a *SessionFile* (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have the Cuvis SDK installed\n", + " - Have Python and the requirements.txt installed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "346872e0-782a-4735-9da0-319f95eb3145", + "metadata": {}, + "outputs": [], + "source": [ + "# If the import of cuvis fails, the most common cause is a mismatch between\n", + "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", + "# Try re-installing both and make sure that the version numbers match exactly\n", + "import cuvis\n", + "import time\n", + "from matplotlib import pyplot as plt\n", + "print(\"Cuvis Python SDK Example 4\")\n", + "\n", + "# Initialize the Cuvis SDK using a settings-directory\n", + "# This is optional (all settings have defaults),\n", + "# but enables you to optimize Cuvis' performance on your system using the settings\n", + "# Your camera and the default Cuvis installation both provide these settings files\n", + "print(\"Initializing Cuvis\")\n", + "cuvis.General.init(\"./settings\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "223ce7ef-57d0-4a98-98eb-66a340757125", + "metadata": {}, + "outputs": [], + "source": [ + "# Enter a path to the SessionFile you want to use\n", + "session_file_path = \"D:/TestMesus/Aquarell/RainbowAquarelleWater_000.cu3s\"\n", + "session_file_path = \"D:/TestMesus/X20P_Cornfields/X20P_flight_data.cu3s\"\n", + "\n", + "# Load the SessionFile\n", + "print(F\"Loading Session File '{session_file_path}'\")\n", + "session = cuvis.SessionFile(session_file_path)\n", + "\n", + "# Load the first measurement of the file\n", + "mesu = session.get_measurement(0)\n", + "print(F\"Loaded measurement at index 0 as {mesu.name}\")" + ] + }, + { + "cell_type": "markdown", + "id": "6c1ed1d4-0b8a-49c1-bb61-d24757ae81d1", + "metadata": {}, + "source": [ + "#### Cube Exporter - Settings (*SaveArgs*)\n", + "When setting up a *CubeExporter* there are many settings to fine-tune the export process and define what gets saved.\n", + "The *SaveArgs* class is used to communicate the settings to the *CubeExporter*.\n", + "\n", + "Here is an overview of the most important attributes of *SaveArgs*:\n", + " - **export_dir**: The directory to export the measurements to\n", + " - **allow_overwrite**: Allow overwriting files in case of a name clash\n", + " - **allow_fragmentation**: Start a new *SessionFile* for each measurement / Allow only one measurement per *SessionFile* \n", + " - **allow_drop**: Allow the exporter to drop measurements if it cannot write to the disk fast enough\n", + " - **allow_info_file**: Create an info file alongside the *SessionFile*. This file contains a list of all measurements in the *SessionFile* and also marks dropped measurements\n", + " - **full_export**: Include the hyperspectral cube when saving to disk. This is **FALSE** by default! *Please note:* The cube can **always be recomputed** on demand from the data stored in the *SessionFile*. Saving the cube can make sense to speed up or allow access to cube data on systems with low or insufficient processing power. It does significantly increase the size of the *SessionFiles*, usually roughly 2x. Additionally, if the cube is included, the processing mode (RAW, Reflectance, ...) is preserved." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa479585-74f2-476c-8fbb-1513b2c98e75", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a CubeExporter with custom settings.\n", + "# Notably: full_export = True \n", + "save_args_full = cuvis.SaveArgs(\n", + " export_dir=\"cube_export\", # Default: \".\"\n", + " allow_overwrite=True, # Default: False\n", + " allow_fragmentation=True, # Default: False\n", + " allow_drop=False, # Default: False\n", + " allow_info_file=True, # Default: True\n", + " full_export=True) # Default: False\n", + "\n", + "cube_exporter_full = cuvis.CubeExporter(save_args_full)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5598cb92-00c9-4326-a120-11c40c592a5d", + "metadata": {}, + "outputs": [], + "source": [ + "# First make sure, that the measurement has a cube\n", + "if mesu.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(mesu)\n", + "\n", + "# Now export a measurement including the cube\n", + "cube_exporter_full.apply(mesu)" + ] + }, + { + "cell_type": "markdown", + "id": "89703cae-1805-43a9-8ecf-446eacc28eb1", + "metadata": {}, + "source": [ + "#### TIFF Exporter\n", + "The *TiffExporter* is used to export hyperspectral cubes (or parts thereof) in *.tiff* (*.tif*) format. As the TIFF format is fairly flexible, three general modes are available:\n", + " - MultiChannel: The cube is stored as a single image in a single file with each wavelength band as a seperate channel\n", + " - MultiPage: The cube is stored as multiple single channel (monochrome) images in a single file. Each wavelength band is a separate \"page\" within the TIFF file.\n", + " - Single: The cube is stored as a multiple single channel (monochrome) image in multiple files. Each wavelength band is a separate TIFF file.\n", + "\n", + "The TIFF export mode is set via the *TiffExportSettings* class when creating the *TiffExporter*. Here is an overview of further useful settings:\n", + " - **export_dir**: The directory to export the measurements to\n", + " - **channel_selection**: Select which wavelength bands are included in the export by their wavelength \\[nm\\] value. This is set via string using a selection syntax. Here are some valid examples:\n", + " - Include only the channel at 400nm: \"400\"\n", + " - Include channels at 400, 410 and 620nm: \"400;410;620\"\n", + " - Include all channels from 400 to 500nm (both exclusive): \"400-500\"\n", + " - Include the channels 400 to 500nm and channel at 600nm: \"400-500;600\"\n", + " - Include all channels: \"all\"\n", + " - Include the channels between 400 and 600nm in 20nm steps: \"400:20:600\"\n", + " - **compression_mode**: Which compression scheme to use. To enable compression, set to `TiffCompressionMode.LZW`.\n", + " - **format**: Which TIFF export mode to use. Default: `TiffFormat.MultiChannel`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3aaaca73-310d-4a79-9cf1-0c154fd7afbc", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a tiff exporter with custom settings\n", + "# Here: Export only the channels between 600nm and 800nm as separate files with compression to directory \"tiff_export\"\n", + "save_args_tiff = cuvis.TiffExportSettings(\n", + " export_dir=\"tiff_export\", # Default: \".\"\n", + " channel_selection=\"600-800\", # Default: \"all\"\n", + " compression_mode=cuvis.TiffCompressionMode.LZW, # Default: TiffCompressionMode.Nothing\n", + " format=cuvis.TiffFormat.Single) # Default: TiffFormat.MultiChannel\n", + "\n", + "tiff_exporter = cuvis.TiffExporter(save_args_tiff)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0db82a3a-8d50-460f-91bc-cf9f6de31ed3", + "metadata": {}, + "outputs": [], + "source": [ + "# First make sure that the measurement has a cube\n", + "if mesu.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(mesu)\n", + "\n", + "# Now export a measurement including the cube to tiff format\n", + "tiff_exporter.apply(mesu)" + ] + }, + { + "cell_type": "markdown", + "id": "03aac6b5-7ce8-4717-abaa-b9205929f845", + "metadata": {}, + "source": [ + "#### ENVI Exporter\n", + "For the *EnviExporter* only some basic settings are available. This exporter will create two files per measurement: A **.hdr** file and a data file with the same name but without a file extension.\n", + "**export_dir** and **channel_selection** apply the same as for *TiffExportSettings* above." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d124b8a1-508f-421a-8afc-33b35753c06c", + "metadata": {}, + "outputs": [], + "source": [ + "# Create an ENVI exporter with custom settings\n", + "save_args_envi = cuvis.EnviExportSettings(\n", + " export_dir=\"envi_export\", # Default: \".\"\n", + " channel_selection=\"all\" # Default: \"all\"\n", + ")\n", + "\n", + "envi_exporter = cuvis.EnviExporter(save_args_envi)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7da59493-c979-4452-a181-bcf4b11bca48", + "metadata": {}, + "outputs": [], + "source": [ + "# First make sure that the measurement has a cube\n", + "if mesu.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(mesu)\n", + "\n", + "# Now export a measurement including the cube to envi format\n", + "envi_exporter.apply(mesu)" + ] + }, + { + "cell_type": "markdown", + "id": "a0100c75-5a72-44e3-b847-c70e9f75b73a", + "metadata": {}, + "source": [ + "#### View Exporter\n", + "The *ViewExporter* enables rendering and exporting views of the cube data, ie. RGB, Color Infrared, or indices like NDVI.\n", + "The views are always RGB images.\n", + "How the view is rendered / computed, is described in using a *UserPlugin* - an XML file with a special syntax that describes data accesses and mathematical operations used to compute the view.\n", + "These files are described in more detail below.\n", + "\n", + "The *ViewExporter* is initialized with the class *ViewExportSettings*, like the other exporters.\n", + "Here is an overview of some useful settings:\n", + " - **export_dir** and **channel_selection**: Same as for *TiffExportSettings* above\n", + " - **userplugin**: Either the path to the *UserPlugin* **.xml** file or a valid XML string of a *UserPlugin*\n", + " - **pan_failback**: Controls the behavior if no cube is available. If **True**, allows using the panchromatic or preview image to be used as a fallback output. Else, throws an exception instead.\n", + "\n", + "#### User Plugins\n", + "The *UserPlugin* is a XML schema definition for how a hyperspectral cube is accessed and processed to compute a regular RGB image from it.\n", + "You can find the XML schema in your Cuvis installation under `Cuvis/user/plugin/userplugin.xsd`\n", + "\n", + "A selection of plugins is provided with your installation of Cuvis under `Cuvis/user/plugin`. The plugins differ slightly between processing modes, as some may only be applicable to, e.g. reflectance data.\n", + "For further information on *UserPlugins*, their syntax and the available operators, please refer to the *Cuvis User Plug-Ins manual* PDF included with your Cuvis installation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4e054685-31f6-4394-a242-b6866b39d5af", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a view exporter with custom settings\n", + "save_args_view = cuvis.ViewExportSettings(\n", + " export_dir=\"view_export\", # Default: \".\"\n", + " channel_selection=\"all\", # Default: \"all\"\n", + " pan_failback=True, # Default: True\n", + " # Please enter the path to your Cuvis installation below\n", + " #userplugin=\"Your Cuvis Install here\" + \"/user/plugin/raw/00_RGB.xml\") # Default: \"\"\n", + " userplugin=\"C:/Program Files/Cuvis/user/plugin/raw/00_RGB.xml\") # Default: \"\"\n", + "\n", + "view_exporter = cuvis.ViewExporter(save_args_view)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "98d3185f-4878-4b30-904e-17557d107fae", + "metadata": {}, + "outputs": [], + "source": [ + "# First make sure that the measurement has a cube\n", + "if mesu.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(mesu)\n", + "\n", + "# Now export a measurement to a rendered view RGB image\n", + "view_exporter.apply(mesu)" + ] + }, + { + "cell_type": "markdown", + "id": "640a918e-dfc3-4e56-b472-65bfadcef21b", + "metadata": {}, + "source": [ + "#### View Exporter - Pansharpening\n", + "This is only applicable to cameras with a separate panchromatic sensor installed (e.g. Ultris X20P).\n", + "\n", + "The process of Pan-Sharpening fuses the hyperspectral cube data (high spectral resolution) with the panchromatic image (high spatial resolution) to create a merged hyperspectral cube with much higher spatial resolution.\n", + "\n", + "Pan-Sharpening can be applied with any exporter by enabling the setting `pre_pan_sharpen_cube` in their respective settings class.\n", + "*Please note*: Applying Pan-Sharpening to the entire cube uses a large amount of system resources and may lead to long processing times!\n", + "\n", + "When using Pan-Sharpening with the *ViewExporter*, the operation can be applied *after* the view is rendered to dramatically reduce the processing overhead. To compute a spectrally more accurate view, the setting `pre_pan_sharpen_cube` can also be used with the *ViewExporter*. \n", + "\n", + "Here is an overview of the settings available that pertain to Pan-Sharpening:\n", + " - **pan_scale**: The \"amount\" of Pan-Sharpening to apply. 0.0 = no Pan-Sharpening. 1.0 = Pan-Sharpen to the resolution of the pan image. 0.5 = Pan-Sharpen to the resolution 50% between the spectral and pan images.\n", + " - **pan_sharpening_interpolation_type**: Which upscaling method to use for resizing operations. Uses `cuvis.PanSharpeningInterpolationType`.\n", + " - **pan_sharpening_algorithm**: Which algorithm to use for the Pan-Sharpening operation. The following are available:\n", + " - `PanSharpeningAlgorithm.None`: Only upscale, no sharpening is applied \n", + " - `PanSharpeningAlgorithm.CubertPanRatio`: Uses the pan sensors White reference for best results. Only applicable in Reflectance processing mode. \n", + " - `PanSharpeningAlgorithm.CubertMacroPixel`: Uses mean brightness information from the pan image to refine the spectral image. Works in all modes without references.\n", + " - **pre_pan_sharpen_cube**: Apply Pan-Sharpening over the entire hyperspectral data cube. *Please note*: Large performance impact!\n", + " - **add_pan**: Whether to include the pan image in the final hyperspectral data cube. It will be labeled as wavelength = 0nm." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "393fb3a5-3e98-4c66-af10-87859ba47250", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a view exporter with pansharpening enabled\n", + "save_args_pansharpen = cuvis.ViewExportSettings(\n", + " export_dir=\"pansharpen_export\", # Default: \".\"\n", + " channel_selection=\"all\", # Default: \"all\"\n", + " pan_scale=1.0, # Default: 0.0\n", + " pan_sharpening_interpolation_type=cuvis.PanSharpeningInterpolationType.Cubic, # Default: Linear \n", + " pan_sharpening_algorithm=cuvis.PanSharpeningAlgorithm.CubertPanRatio, # Default: CubertMacroPixel\n", + " pre_pan_sharpen_cube=False, # Default: False \n", + " add_pan=False, # Default: False\n", + " pan_failback=True, # Default: True\n", + " # Please enter the path to your Cuvis installation below\n", + " #userplugin=\"Your Cuvis Install here\" + \"/user/plugin/raw/00_RGB.xml\") # Default: \"\"\n", + " userplugin=\"C:/Program Files/Cuvis/user/plugin/raw/00_RGB.xml\") # Default: \"\"\n", + "\n", + "pansharpen_exporter = cuvis.ViewExporter(save_args_pansharpen)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f4a3af1f-0044-4d75-8319-d04a652c3989", + "metadata": {}, + "outputs": [], + "source": [ + "# First make sure that the measurement has a cube\n", + "if mesu.processing_mode == cuvis.ProcessingMode.Preview:\n", + " pc = cuvis.ProcessingContext(session)\n", + " pc.processing_mode = cuvis.ProcessingMode.Raw\n", + " pc.apply(mesu)\n", + "\n", + "# Now export a measurement to a pan-sharpened rendered view RGB image\n", + "pansharpen_exporter.apply(mesu)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b0b8f9d2-3cd0-4fd9-ad5e-cd03d360a9e2", + "metadata": {}, + "outputs": [], + "source": [ + "cuvis.SaveArgs?" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/README.md b/README.md index 901c61d..aff1dda 100644 --- a/README.md +++ b/README.md @@ -2,47 +2,4 @@ # cuvis.python.examples -## Running the examples -To get the exampels running, first set up a project directory with (probably) an own environment and clone this git repository there. - -Then, you need to install the Cuvis C SDK (see [here](https://cloud.cubert-gmbh.de/s/qpxkyWkycrmBK9m), as explained for the python wrapper [here](https://github.com/cubert-hyperspectral/cuvis.python). - -Then you can simply install the required dependencies using pip in your local project environment. - -``` -pip install -r requirements.txt -``` - -Alternatively to pip, take a look on how to install the python wrapper manually [here](https://github.com/cubert-hyperspectral/cuvis.python). - -For running some of the examples, you have to use sample data (provided [here](https://cloud.cubert-gmbh.de/s/SrkSRja5FKGS2Tw?path=%2FCuvis%203.2%20Sample%20Data)). - -## Inventory - -### 01_loadMeasurement -Load measurement from disk and print the value (count) for all available channels (wavelength) for one specific pixel. - -### 02_reprocessMeasurement -Load measurement as well as references (dark, white, distance) from disk and reprocess the measurement to reflectance. - -### 03_exportMeasurement -Load measurement from disk and save to different file formats. - -### 04_changeDistance -Load measurement from disk and reprocess to a new given distance. - -### 05_recordSingleImages -Setup camera and record measurements via looping software trigger, aka -"single shot mode" or "software mode". - -### 05_recordSingleImages_async -Same as example 05_recordSingleImages but with `asyncio`. - -### 06_recordVideo -Setup camera and record measurements via internal clock triggering, aka "video mode". In this example the `cuvis.Worker` is used to make use of multithreading (`cuvis_worker_create`). - -### 06_recordVideo_async -Same as example 06_recordVideo but with `asyncio`. - -### 07_recordVideoFromSessionFile -Set up a virtual camera based on a pre-recorded session file to simulate actual camera behaviour. +TODO \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index fcd400c..f4c4675 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,3 @@ cuvis -matplotlib \ No newline at end of file +matplotlib +notebook \ No newline at end of file From 5e0e37d207527fb05627c82aa36aa00f76a0982d Mon Sep 17 00:00:00 2001 From: Philip Manke Date: Wed, 3 Sep 2025 16:53:13 +0200 Subject: [PATCH 03/11] Add Example 5, default settings and some plugins --- Example_1_Take_Snapshot.ipynb | 14 +- Example_2_Load_Measurement.ipynb | 4 +- Example_3_Reprocess.ipynb | 14 +- Example_4_Exporters.ipynb | 57 ++--- Example_5_Record_Video.ipynb | 379 +++++++++++++++++++++++++++++++ factory/.gitkeep | 0 plugins/00_RGB.xml | 90 ++++++++ plugins/01_CIR.xml | 20 ++ plugins/02_SWIR.xml | 20 ++ plugins/03_mono.xml | 35 +++ plugins/SAMRGB.xml | 82 +++++++ requirements.txt | 4 +- settings/core.settings | 54 +++++ settings/cuvis.settings | 135 +++++++++++ settings/system.settings | 13 ++ settings/ultris20.settings | 20 ++ settings/ultris20plus.settings | 26 +++ settings/ultris5.settings | 30 +++ 18 files changed, 946 insertions(+), 51 deletions(-) create mode 100644 Example_5_Record_Video.ipynb create mode 100644 factory/.gitkeep create mode 100644 plugins/00_RGB.xml create mode 100644 plugins/01_CIR.xml create mode 100644 plugins/02_SWIR.xml create mode 100644 plugins/03_mono.xml create mode 100644 plugins/SAMRGB.xml create mode 100644 settings/core.settings create mode 100644 settings/cuvis.settings create mode 100644 settings/system.settings create mode 100644 settings/ultris20.settings create mode 100644 settings/ultris20plus.settings create mode 100644 settings/ultris5.settings diff --git a/Example_1_Take_Snapshot.ipynb b/Example_1_Take_Snapshot.ipynb index 83cdd18..62dc164 100644 --- a/Example_1_Take_Snapshot.ipynb +++ b/Example_1_Take_Snapshot.ipynb @@ -15,7 +15,7 @@ " - *SessionFile* as camera calibration file\n", " - *CubeExporter* for saving measurements\n", "\n", - "**Step-by-Step overview for this example:**\n", + "**Step-by-Step outline:**\n", " 1. Import and initialize Cuvis SDK\n", " 2. Load the calibration file for your camera using *SessionFile*\n", " 3. Connect and initialize your camera using the *AcquisitionContext*\n", @@ -23,8 +23,8 @@ " 5. Save the measurement to disk using the *CubeExporter*\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a camera connected *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", - " - Have the camera calibration file (*SN*.cu3c) ready *or* use the [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have a camera connected *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", + " - Have the camera calibration file (*SN*.cu3c) ready *or* use the [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", " - Have the Cuvis SDK installed\n", " - Have Python and the requirements.txt installed" ] @@ -65,7 +65,7 @@ "camera_serial_number_str = \"Your camera serial here\"\n", "\n", "# If using demo data instead of a physical camera, change this to your download location:\n", - "demo_session_file = \"Your download location here /Lentils_2.0_XMR/Lentils_000.cu3s\"\n", + "demo_session_file = \"/SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", "\n", "camera_calibration_file_path = F\"./factory/{camera_serial_number_str}.cu3c\"" ] @@ -208,9 +208,9 @@ "metadata": {}, "source": [ "#### Capturing a Measurement with Software Trigger (Single Snapshot)\n", - "Using the *capture()* method, a single measurement is initiated.\n", - "Taking a snapshot requires some time, so, to prevent the call to *capture()* from blocking execution, an *AsyncMesu* is returned.\n", - "To await the completion of the snapshot, use the *get()* method on the *AsyncMesu*. " + "Using the `capture()` method, a single measurement is initiated.\n", + "Taking a snapshot requires some time, so, to prevent the call to `capture()` from blocking execution, an *AsyncMesu* is returned.\n", + "To await the completion of the snapshot, use the `get()` method on the *AsyncMesu*. " ] }, { diff --git a/Example_2_Load_Measurement.ipynb b/Example_2_Load_Measurement.ipynb index e3baefa..af713b3 100644 --- a/Example_2_Load_Measurement.ipynb +++ b/Example_2_Load_Measurement.ipynb @@ -23,7 +23,7 @@ " 5. Access data and meta-data from a single *Measurement*\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", " - Have the Cuvis SDK installed\n", " - Have Python and the requirements.txt installed" ] @@ -75,7 +75,7 @@ "outputs": [], "source": [ "# Enter a path applicable to your setup here\n", - "session_file_path = \"D:/TestMesus/Aquarium/Auto_004.cu3s\"\n", + "session_file_path = \"./SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", "\n", "# Load the SessionFile\n", "print(F\"Loading Session File '{session_file_path}'\")\n", diff --git a/Example_3_Reprocess.ipynb b/Example_3_Reprocess.ipynb index 7639ba6..a3c568e 100644 --- a/Example_3_Reprocess.ipynb +++ b/Example_3_Reprocess.ipynb @@ -16,7 +16,7 @@ " - *Measurement* to access the SessionFiles data and meta-data\n", " - *ProcessingContext* to generate hyperspectral cubes using different processing modes\n", "\n", - "**Step-by-Step overview for this example:**\n", + "**Step-by-Step outline:**\n", " 1. Import and initialize Cuvis SDK\n", " 2. Load the recorded measurement file using *SessionFile*\n", " 3. Extract a *Measurement* from the *SessionFile*\n", @@ -24,8 +24,8 @@ " 5. Use *ProcessingContext* to generate hyperspectral cubes\n", "\n", "**Prerequisites to running this example:**\n", - " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", - " - Have a recorded White and Dark reference measurement *or* use the [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have a recorded measurement in *SessionFile* format (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", + " - Have a recorded White and Dark reference measurement *or* use the [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", " - Have the Cuvis SDK installed\n", " - Have Python and the requirements.txt installed" ] @@ -180,10 +180,10 @@ "\n", "To generate a hyperspectral cube, the *ProcessingContext* is **applied** to the *Measurement*. The *Measurement* is modified **in-place** and now contains a cube.\n", "\n", - "To select the processing mode, write the **processing_mode** attribute.\n", + "To select the processing mode, write the `processing_mode` attribute.\n", "\n", "When initializing a *ProcessingContext* from a *SessionFile*, the reference *Measurements* stored in the *SessionFile* are automatically loaded and set within the *ProcessingContext*.\n", - "Using the method *set_reference*, different measurements can be set for each reference type." + "Using the method `set_reference`, different measurements can be set for each reference type." ] }, { @@ -373,10 +373,10 @@ "processing_context.apply(measurement)\n", "\n", "# Show data\n", - "# Note: The Viewer will be explained in detail in Example 5\n", + "# Note: The Viewer is explained in detail in Example 5\n", "# It is used here to generate an RGB view of the measurement as\n", "# the effect of Distance calibration is not visible by only observing a single channel\n", - "viewer = cuvis.Viewer(cuvis.ViewerSettings(userplugin=\"Your Cuvis Install Dir here\" + \"/user/plugin/ref/00_RGB.xml\"))\n", + "viewer = cuvis.Viewer(cuvis.ViewerSettings(userplugin=\"./plugins/00_RGB.xml\"))\n", "view_nodistance = viewer.apply(measurement)\n", "\n", "# Set distance reference\n", diff --git a/Example_4_Exporters.ipynb b/Example_4_Exporters.ipynb index b3ad369..e945bab 100644 --- a/Example_4_Exporters.ipynb +++ b/Example_4_Exporters.ipynb @@ -18,7 +18,7 @@ " - *ViewExporter* for exporting rendered views of the data\n", " - *UserPlugins* to define how a view is computed\n", "\n", - "**Step-by-Step overview for this example:**\n", + "**Step-by-Step outline:**\n", " 1. Load measurements from a *SessionFile*\n", " 2. Re-export as a *SessionFile* with different settings\n", " 3. Export to TIFF\n", @@ -27,7 +27,7 @@ " 6. Export a rendered view of a measurement as described by a *UserPlugin*\n", "\n", "**Prerequisites to running this example:**\n", - " - Have recorded a *SessionFile* (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1xDqMipIm5j7leWOoHiFu2KuKjSzqlBR9)\n", + " - Have recorded a *SessionFile* (.cu3s) *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", " - Have the Cuvis SDK installed\n", " - Have Python and the requirements.txt installed" ] @@ -63,8 +63,7 @@ "outputs": [], "source": [ "# Enter a path to the SessionFile you want to use\n", - "session_file_path = \"D:/TestMesus/Aquarell/RainbowAquarelleWater_000.cu3s\"\n", - "session_file_path = \"D:/TestMesus/X20P_Cornfields/X20P_flight_data.cu3s\"\n", + "session_file_path = \"SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", "\n", "# Load the SessionFile\n", "print(F\"Loading Session File '{session_file_path}'\")\n", @@ -85,12 +84,12 @@ "The *SaveArgs* class is used to communicate the settings to the *CubeExporter*.\n", "\n", "Here is an overview of the most important attributes of *SaveArgs*:\n", - " - **export_dir**: The directory to export the measurements to\n", - " - **allow_overwrite**: Allow overwriting files in case of a name clash\n", - " - **allow_fragmentation**: Start a new *SessionFile* for each measurement / Allow only one measurement per *SessionFile* \n", - " - **allow_drop**: Allow the exporter to drop measurements if it cannot write to the disk fast enough\n", - " - **allow_info_file**: Create an info file alongside the *SessionFile*. This file contains a list of all measurements in the *SessionFile* and also marks dropped measurements\n", - " - **full_export**: Include the hyperspectral cube when saving to disk. This is **FALSE** by default! *Please note:* The cube can **always be recomputed** on demand from the data stored in the *SessionFile*. Saving the cube can make sense to speed up or allow access to cube data on systems with low or insufficient processing power. It does significantly increase the size of the *SessionFiles*, usually roughly 2x. Additionally, if the cube is included, the processing mode (RAW, Reflectance, ...) is preserved." + " - `export_dir`: The directory to export the measurements to\n", + " - `allow_overwrite`: Allow overwriting files in case of a name clash\n", + " - `allow_fragmentation`: Start a new *SessionFile* for each measurement / Allow only one measurement per *SessionFile* \n", + " - `allow_drop`: Allow the exporter to drop measurements if it cannot write to the disk fast enough\n", + " - `allow_info_file`: Create an info file alongside the *SessionFile*. This file contains a list of all measurements in the *SessionFile* and also marks dropped measurements\n", + " - `full_export`: Include the hyperspectral cube when saving to disk. This is **FALSE** by default! *Please note:* The cube can **always be recomputed** on demand from the data stored in the *SessionFile*. Saving the cube can make sense to speed up or allow access to cube data on systems with low or insufficient processing power. It does significantly increase the size of the *SessionFiles*, usually roughly 2x. Additionally, if the cube is included, the processing mode (RAW, Reflectance, ...) is preserved." ] }, { @@ -142,16 +141,16 @@ " - Single: The cube is stored as a multiple single channel (monochrome) image in multiple files. Each wavelength band is a separate TIFF file.\n", "\n", "The TIFF export mode is set via the *TiffExportSettings* class when creating the *TiffExporter*. Here is an overview of further useful settings:\n", - " - **export_dir**: The directory to export the measurements to\n", - " - **channel_selection**: Select which wavelength bands are included in the export by their wavelength \\[nm\\] value. This is set via string using a selection syntax. Here are some valid examples:\n", + " - `export_dir`: The directory to export the measurements to\n", + " - `channel_selection`: Select which wavelength bands are included in the export by their wavelength \\[nm\\] value. This is set via string using a selection syntax. Here are some valid examples:\n", " - Include only the channel at 400nm: \"400\"\n", " - Include channels at 400, 410 and 620nm: \"400;410;620\"\n", " - Include all channels from 400 to 500nm (both exclusive): \"400-500\"\n", " - Include the channels 400 to 500nm and channel at 600nm: \"400-500;600\"\n", " - Include all channels: \"all\"\n", " - Include the channels between 400 and 600nm in 20nm steps: \"400:20:600\"\n", - " - **compression_mode**: Which compression scheme to use. To enable compression, set to `TiffCompressionMode.LZW`.\n", - " - **format**: Which TIFF export mode to use. Default: `TiffFormat.MultiChannel`" + " - `compression_mode`: Which compression scheme to use. To enable compression, set to `TiffCompressionMode.LZW`.\n", + " - `format`: Which TIFF export mode to use. Default: `TiffFormat.MultiChannel`" ] }, { @@ -195,8 +194,8 @@ "metadata": {}, "source": [ "#### ENVI Exporter\n", - "For the *EnviExporter* only some basic settings are available. This exporter will create two files per measurement: A **.hdr** file and a data file with the same name but without a file extension.\n", - "**export_dir** and **channel_selection** apply the same as for *TiffExportSettings* above." + "For the *EnviExporter* only some basic settings are available. This exporter will create two files per measurement: A `.hdr` file and a data file with the same name but without a file extension.\n", + "`export_dir` and `channel_selection` apply the same as for *TiffExportSettings* above." ] }, { @@ -245,9 +244,9 @@ "\n", "The *ViewExporter* is initialized with the class *ViewExportSettings*, like the other exporters.\n", "Here is an overview of some useful settings:\n", - " - **export_dir** and **channel_selection**: Same as for *TiffExportSettings* above\n", - " - **userplugin**: Either the path to the *UserPlugin* **.xml** file or a valid XML string of a *UserPlugin*\n", - " - **pan_failback**: Controls the behavior if no cube is available. If **True**, allows using the panchromatic or preview image to be used as a fallback output. Else, throws an exception instead.\n", + " - `export_dir` and `channel_selection`: Same as for *TiffExportSettings* above\n", + " - `userplugin`: Either the path to the *UserPlugin* `.xml` file or a valid XML string of a *UserPlugin*\n", + " - `pan_failback`: Controls the behavior if no cube is available. If `True`, allows using the panchromatic or preview image to be used as a fallback output. Else, throws an exception instead.\n", "\n", "#### User Plugins\n", "The *UserPlugin* is a XML schema definition for how a hyperspectral cube is accessed and processed to compute a regular RGB image from it.\n", @@ -309,14 +308,14 @@ "When using Pan-Sharpening with the *ViewExporter*, the operation can be applied *after* the view is rendered to dramatically reduce the processing overhead. To compute a spectrally more accurate view, the setting `pre_pan_sharpen_cube` can also be used with the *ViewExporter*. \n", "\n", "Here is an overview of the settings available that pertain to Pan-Sharpening:\n", - " - **pan_scale**: The \"amount\" of Pan-Sharpening to apply. 0.0 = no Pan-Sharpening. 1.0 = Pan-Sharpen to the resolution of the pan image. 0.5 = Pan-Sharpen to the resolution 50% between the spectral and pan images.\n", - " - **pan_sharpening_interpolation_type**: Which upscaling method to use for resizing operations. Uses `cuvis.PanSharpeningInterpolationType`.\n", - " - **pan_sharpening_algorithm**: Which algorithm to use for the Pan-Sharpening operation. The following are available:\n", + " - `pan_scale`: The \"amount\" of Pan-Sharpening to apply. 0.0 = no Pan-Sharpening. 1.0 = Pan-Sharpen to the resolution of the pan image. 0.5 = Pan-Sharpen to the resolution 50% between the spectral and pan images.\n", + " - `pan_sharpening_interpolation_type`: Which upscaling method to use for resizing operations. Uses `cuvis.PanSharpeningInterpolationType`.\n", + " - `pan_sharpening_algorithm`: Which algorithm to use for the Pan-Sharpening operation. The following are available:\n", " - `PanSharpeningAlgorithm.None`: Only upscale, no sharpening is applied \n", " - `PanSharpeningAlgorithm.CubertPanRatio`: Uses the pan sensors White reference for best results. Only applicable in Reflectance processing mode. \n", " - `PanSharpeningAlgorithm.CubertMacroPixel`: Uses mean brightness information from the pan image to refine the spectral image. Works in all modes without references.\n", - " - **pre_pan_sharpen_cube**: Apply Pan-Sharpening over the entire hyperspectral data cube. *Please note*: Large performance impact!\n", - " - **add_pan**: Whether to include the pan image in the final hyperspectral data cube. It will be labeled as wavelength = 0nm." + " - `pre_pan_sharpen_cube`: Apply Pan-Sharpening over the entire hyperspectral data cube. *Please note*: Large performance impact!\n", + " - `add_pan`: Whether to include the pan image in the final hyperspectral data cube. It will be labeled as wavelength = 0nm." ] }, { @@ -359,16 +358,6 @@ "# Now export a measurement to a pan-sharpened rendered view RGB image\n", "pansharpen_exporter.apply(mesu)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b0b8f9d2-3cd0-4fd9-ad5e-cd03d360a9e2", - "metadata": {}, - "outputs": [], - "source": [ - "cuvis.SaveArgs?" - ] } ], "metadata": { diff --git a/Example_5_Record_Video.ipynb b/Example_5_Record_Video.ipynb new file mode 100644 index 0000000..3f7c743 --- /dev/null +++ b/Example_5_Record_Video.ipynb @@ -0,0 +1,379 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0fb5dbc7-d3d4-4963-a0b5-0a6db821707a", + "metadata": {}, + "source": [ + "# Cuvis Python SDK Example 5\n", + "## Record and Show a Video using the Worker Class\n", + "\n", + "This example applies principles introduced in the previous examples to set up a comprehensive real-time hyperspectral video recording and processing pipeline.\n", + "The *Worker* class is introduced, which enables efficient use of the classes needed to acquire, process and save measurements.\n", + "\n", + "**Used principles:**\n", + " - *SessionFile* to load a camera calibration\n", + " - *AcquisitionContext* to communicate with the camera and acquire measurments\n", + " - *ProcessingContext* to compute hyperspectral cubes\n", + " - *CubeExporter* to save measurements to disk\n", + " - *Viewer* to generate visualizations of the hyperspectral cube\n", + " - *Userplugin* to define the visualization of the hyperspectral cube\n", + " - *Worker* to tie everything together to a managed processing pipeline\n", + "\n", + "**Step-by-Step outline:**\n", + " 1. Import and initialize Cuvis SDK\n", + " 2. Load the calibration file for your camera using *SessionFile*\n", + " 3. Connect and initialize your camera using the *AcquisitionContext*\n", + " 4. Set up the computation of the hyperspectral cubes using *ProcessingContext*\n", + " 5. Set up saving to disk of the video using *CubeExporter*\n", + " 6. Set up the visualization of the measurements using *Viewer* and *Userplugin*\n", + " 7. Configure the processing and recording pipeline using *Worker*\n", + " 8. Record a hyperspectral video \n", + "\n", + "**Prerequisites to running this example:**\n", + " - Have a camera connected *or* downloaded the provided [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", + " - Have the camera calibration file (*SN*.cu3c) ready *or* use the [demo data](https://drive.google.com/drive/folders/1Cjb0v_a2p1cCmhKH8w2OuRtnhXCJGz61?usp=sharing)\n", + " - Have the Cuvis SDK installed\n", + " - Have Python and the requirements.txt installed" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4dda1713-292f-4a9e-9e9a-f2940d39c224", + "metadata": {}, + "outputs": [], + "source": [ + "#%matplotlib widget\n", + "# If the import of cuvis fails, the most common cause is a mismatch between\n", + "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", + "# Try re-installing both and make sure that the version numbers match exactly\n", + "import cuvis\n", + "import time\n", + "import io\n", + "import os\n", + "import numpy as np\n", + "import ipywidgets as widgets\n", + "from IPython.display import display\n", + "from PIL import Image as PILImage\n", + "print(\"Cuvis Python SDK Example 5\")\n", + "\n", + "# Initialize the Cuvis SDK using a settings-directory\n", + "# This is optional (all settings have defaults),\n", + "# but enables you to optimize Cuvis' performance on your system using the settings\n", + "# Your camera and the default Cuvis installation both provide these settings files\n", + "print(\"Initializing Cuvis\")\n", + "cuvis.General.init(\"./settings\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0a21c45-c78e-47d4-a879-c5ae3feb67d8", + "metadata": {}, + "outputs": [], + "source": [ + "# Video recording setup / User input\n", + "# Enter your data here!\n", + "video_integration_time_ms = 100\n", + "video_fps = 2\n", + "video_number = 1 # For naming the video files\n", + "video_processing_mode = cuvis.ProcessingMode.Raw\n", + "visualization_user_plugin_path = \"./plugins/00_RGB.xml\"\n", + "enable_pansharpening = True\n", + "save_directory = \"./directory to save the measurements to here\"\n", + "video_filename = \"MyHyperspectralVideo\"\n", + "camera_serial_number_str = \"Your Cameras Serial Number\"\n", + "\n", + "# If using demo data instead of a physical camera, change this to your download location:\n", + "demo_session_file = \"./SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", + "\n", + "camera_calibration_file_path = F\"./factory/{camera_serial_number_str}.cu3c\"" + ] + }, + { + "cell_type": "markdown", + "id": "084aad0a-a2b5-4510-8a80-1dcb6645994f", + "metadata": {}, + "source": [ + "#### Set up Camera\n", + "- Load calibration file\n", + "- Initialize *AcquisitionContext*\n", + "- Wait for camera to report **ready**\n", + "- Parametrize *AcquisitionContext* with recording parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "19722990-c50b-41ed-b1a5-9cfef8aac95a", + "metadata": {}, + "outputs": [], + "source": [ + "# If working with a physical camera, use these two lines\n", + "calib = cuvis.SessionFile(camera_calibration_file_path)\n", + "acq_cont = cuvis.AcquisitionContext(calib)\n", + "\n", + "# If you don't have a physical camera and want to simulate one, use these two lines. Uncomment the above\n", + "#calib = cuvis.SessionFile(demo_session_file)\n", + "#acq_cont = cuvis.AcquisitionContext(calib, simulate=True)\n", + "\n", + "# Wait for camera connection to be established\n", + "print(\"Connecting with camera\")\n", + "while(not acq_cont.ready):\n", + " time.sleep(1)\n", + " print(\".\", end=\"\")\n", + "print(\"\\nCamera connected!\")\n", + "time.sleep(0.5)\n", + "# Set up recording parameters\n", + "acq_cont.operation_mode = cuvis.OperationMode.Internal\n", + "acq_cont.set_continuous(False) # Pause video stream for now\n", + "acq_cont.integration_time = video_integration_time_ms\n", + "acq_cont.fps = video_fps\n", + "print(\"Camera ready!\")" + ] + }, + { + "cell_type": "markdown", + "id": "7bf2548e-cbb3-491e-9529-3a7747a0b5c0", + "metadata": {}, + "source": [ + "#### Set up ProcessingContext and Export\n", + "- Initialize and configure *ProcessingContext*\n", + "- Create and configure *CubeExporter*" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3383fb7e-1dd4-45aa-b8ff-3451986c3366", + "metadata": {}, + "outputs": [], + "source": [ + "# Create ProcessingContext\n", + "print(\"Loading processing context...\")\n", + "proc_cont = cuvis.ProcessingContext(calib)\n", + "proc_cont.processing_mode = video_processing_mode\n", + "print(\"Done!\")\n", + "\n", + "# Create CubeExporter\n", + "save_args = cuvis.SaveArgs(\n", + " export_dir=save_directory,\n", + " allow_overwrite=True,\n", + " full_export=False,\n", + " allow_drop=True)\n", + "cube_exporter = cuvis.CubeExporter(save_args)" + ] + }, + { + "cell_type": "markdown", + "id": "514120c4-80fb-42fb-999f-9dd441a1c044", + "metadata": {}, + "source": [ + "#### Viewer\n", + "This class uses a *Userplugin* file to compute visualizations (RGB images) of hyperspectral input data (cubes).\n", + "The *Viewer* is almost the same thing as the *ViewExporter* introduced in **Example 04 - Exporters**.\n", + "The only real difference is: The *ViewExporter* immediately writes the generated visualizations to disk as `.tiff` files while the *Viewer* returns these images in memory for immediate use in your application.\n", + "The results are returned using the class *ImageData*.\n", + "*ImageData* contains the following attributes:\n", + " - `width`, `height` and `channels`, define the image's dimensions\n", + " - `array` points to the actual data as a **numpy** array\n", + " - `wavelength` is a list that maps the image's channels to a physical wavelength, if applicable\n", + "\n", + "The *Viewer* is configured similarly to the *ViewExporter* with some differences.\n", + "Here is an overview of some useful settings:\n", + " - `userplugin`: Either the path to the *UserPlugin* `.xml` file or a valid XML string of a *UserPlugin*\n", + " - `pan_failback`: Controls the behavior if no cube is available. If `True`, allows using the panchromatic or preview image to be used as a fallback output. Else, throws an exception instead.\n", + " - Pan Sharpening Settings (`pan_scale`, `pan_sharpening_interpolation_type`, `pan_sharpening_algorithm`, `pre_pan_sharpen_cube`): See Example 4" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d8182df-3592-4936-8712-c37c4bf11705", + "metadata": {}, + "outputs": [], + "source": [ + "# Create Viewer\n", + "view_args = cuvis.ViewerSettings(\n", + " userplugin=visualization_user_plugin_path,\n", + " pan_scale=1.0 if enable_pansharpening else 0.0)\n", + "viewer = cuvis.Viewer(view_args)" + ] + }, + { + "cell_type": "markdown", + "id": "40f28896-61bb-436a-922c-6ead34b67b51", + "metadata": {}, + "source": [ + "#### Worker\n", + "The *Worker* is a class that implements a processing and/or recording pipeline.\n", + "It manages the acquisition of measurements from the *AcquisitionContext* and manages handing them to further processing and/or exporting steps as you define them.\n", + "This allows your application code to avoid dealing with asynchronous processing and resource management (compute, threads).\n", + "Using settings files and paramters in its constructor, you can define some characteristics of the *Worker*, eg. how many threads it will occupy at maximum.\n", + "\n", + "A typical *Worker* setup looks like this:\n", + "\n", + "Worker`[AcquisitionContext -> CubeExporter -> ProcessingContext -> Viewer]`-> View Results\n", + "\n", + "Alternatively, measurements can be \"manually\" inserted into the *Worker*. For this to work, the *Worker* must not have an *AcquisitionContext* set and the `input_queue_size` must be set to larger than zero.\n", + "\n", + "The following settings are available for the *Worker*:\n", + "- `input_queue_size`: When not using an *AcquisitionContext* as the source of measurements, you can also **ingest** measurements directly into the *Worker*. This parameter defines the size of the input queue for \"manually\" inserted measurements.\n", + "- `mandatory_queue_size`: Defines the number of measurements that can be processed at the same time. This \"work pool\" handles the \"mandatory\" steps, like exporting and computing the hyperspectral cube.\n", + "- `supplementary_queue_size`: Generally should be set to the same value as `mandatory_queue_size`. This \"work pool\" handles the \"supplementary\" steps, such as view generation and computing the hyperspectral cube, if the cube is not required for the export step. \n", + "- `output_queue_size`: The number of measurements that the *Worker* will hold onto in its output buffer, before dropping or stalling. Should at least be `mandatory_queue_size` + `supplementary_queue_size` + 1.\n", + "- `can_skip_measurements`: Whether incoming measurements can be dropped if the input queue is full.\n", + "- `can_skip_supplementary_steps`: Whether measurements can be dropped after they have been exported if the system is overloaded.\n", + "- `can_drop_results`: Whether results (processed measurements) can be dropped if the output buffer is full." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b0e517cc-d86d-428b-a748-16001a1e7c87", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a Worker\n", + "worker_args = cuvis.WorkerSettings(\n", + " input_queue_size=0, # Default: 0\n", + " mandatory_queue_size=2, # Default: 4\n", + " supplementary_queue_size=2, # Default: 4\n", + " output_queue_size=10, # Default: 10\n", + " can_skip_measurements=True, # Default: False\n", + " can_skip_supplementary_steps=True, # Default: True\n", + " can_drop_results=True) # Default: True\n", + "worker = cuvis.Worker(worker_args)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef4b65d2-a5db-4724-9918-84e34c6b818f", + "metadata": {}, + "outputs": [], + "source": [ + "# Configure the worker\n", + "worker.set_acquisition_context(acq_cont)\n", + "worker.set_processing_context(proc_cont)\n", + "worker.set_exporter(cube_exporter)\n", + "worker.set_viewer(viewer)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a40fdd9c-beec-4818-8d17-1e74607c0c4e", + "metadata": {}, + "outputs": [], + "source": [ + "# Helper Function\n", + "def show_next_frame(frame, fmt='jpeg', jpeg_quality=85):\n", + " arr = np.asarray(frame)\n", + " if arr.ndim == 2:\n", + " arr = np.repeat(arr[..., None], 3, axis=2)\n", + " if arr.shape[-1] == 4:\n", + " arr = arr[..., :3]\n", + " if arr.dtype != np.uint8:\n", + " arr = np.clip(arr, 0, 255).astype(np.uint8)\n", + "\n", + " buf = io.BytesIO()\n", + " if fmt == 'jpeg':\n", + " PILImage.fromarray(arr).save(buf, format='JPEG', quality=jpeg_quality)\n", + " else:\n", + " PILImage.fromarray(arr).save(buf, format='PNG')\n", + " img.value = buf.getvalue()" + ] + }, + { + "cell_type": "markdown", + "id": "f14cb35c-dedf-4f9f-b785-db37afdd43f9", + "metadata": {}, + "source": [ + "#### Run Worker Pipeline\n", + "\n", + "To start/stop the worker pipeline, a simple procedure should be followed to avoid measurements being stuck in buffers or queues.\n", + "\n", + "Starting the pipeline:\n", + " 1. Start the *Worker*\n", + " 2. Start the video stream of the camera\n", + "\n", + "Stopping the pipeline:\n", + " 1. Stop the video stream of the camera\n", + " 2. Stop the *Worker*\n", + " 3. Clear all measurements from the *Worker*" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6af5262a-653f-474f-bddb-d5a8c419efcb", + "metadata": {}, + "outputs": [], + "source": [ + "# Video duration in seconds\n", + "video_duration_s = 10\n", + "\n", + "print(\"Starting pipeline...\")\n", + "worker.start_processing()\n", + "# Name the video\n", + "acq_cont.session_info = cuvis.SessionData(video_filename, video_number, 0)\n", + "acq_cont.set_continuous(True)\n", + "\n", + "# Show image in notebook\n", + "img = widgets.Image(format='jpeg') # or 'png'\n", + "img.layout = widgets.Layout(border='1px solid #ddd', width='auto')\n", + "display(img)\n", + "\n", + "print(\"Acquiring...\")\n", + "# Run recording for video_duration_s seconds\n", + "start_time_ns = time.time_ns()\n", + "end_time_ns = start_time_ns + video_duration_s * 1e9 # convert to ns\n", + "while time.time_ns() < end_time_ns:\n", + " # Check if worker has a result\n", + " if worker.has_next_result():\n", + " # Fetch and display it \n", + " result = worker.get_next_result(timeout=100) # timeout is in ms\n", + " show_next_frame(result.view.array)\n", + " else:\n", + " time.sleep(0.1)\n", + "\n", + "print(\"Stopping pipeline...\")\n", + "acq_cont.set_continuous(False)\n", + "worker.stop_processing()\n", + "worker.drop_all_queued()\n", + "\n", + "# Check recorded file\n", + "filepath = os.path.join(save_directory, video_filename + F\"_{video_number:03}.cu3s\")\n", + "video_number += 1\n", + "if not os.path.exists(filepath):\n", + " print(\"Video file not found...\")\n", + "else:\n", + " sess = cuvis.SessionFile(filepath)\n", + " print(F\"Recorded {sess.get_size()} measurements in file: {filepath}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/factory/.gitkeep b/factory/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/plugins/00_RGB.xml b/plugins/00_RGB.xml new file mode 100644 index 0000000..6d79a6c --- /dev/null +++ b/plugins/00_RGB.xml @@ -0,0 +1,90 @@ + + + + + RGB View with adjustable bandwidths using manual fastmono channels: + --- + Red := avg(RedWL ± Width/2) + Green := avg(GreenWL ± Width/2) + Blue := avg(BlueWL ± Width/2) + + + 650 + 550 + 470 + 20 + 0.75 + + + + + + 2 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/plugins/01_CIR.xml b/plugins/01_CIR.xml new file mode 100644 index 0000000..50051bb --- /dev/null +++ b/plugins/01_CIR.xml @@ -0,0 +1,20 @@ + + + + + 780 + 1000 + 630 + 700 + 490 + 560 + 0.75 + + + + + + + + + \ No newline at end of file diff --git a/plugins/02_SWIR.xml b/plugins/02_SWIR.xml new file mode 100644 index 0000000..c40e48a --- /dev/null +++ b/plugins/02_SWIR.xml @@ -0,0 +1,20 @@ + + + + + 1400 + 1500 + 1200 + 1300 + 1000 + 1100 + 0.75 + + + + + + + + + \ No newline at end of file diff --git a/plugins/03_mono.xml b/plugins/03_mono.xml new file mode 100644 index 0000000..5f2afce --- /dev/null +++ b/plugins/03_mono.xml @@ -0,0 +1,35 @@ + + + + + A simple monochromatic viewer with averaging over a central wavelength. + + 0.75 + 500 + 5 + + + + + 2 + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/plugins/SAMRGB.xml b/plugins/SAMRGB.xml new file mode 100644 index 0000000..ea9644a --- /dev/null +++ b/plugins/SAMRGB.xml @@ -0,0 +1,82 @@ + + + + + + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1; + 1;1;1;1;1;1;1;1;1;1 + + + 2 + 0.9 + 400 + 1550 + + 590 + 700 + 500 + 570 + 440 + 500 + 0.75 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index f4c4675..e577559 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,3 +1,5 @@ cuvis matplotlib -notebook \ No newline at end of file +notebook +ipympl +ipywidgets \ No newline at end of file diff --git a/settings/core.settings b/settings/core.settings new file mode 100644 index 0000000..5eec8d4 --- /dev/null +++ b/settings/core.settings @@ -0,0 +1,54 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/settings/cuvis.settings b/settings/cuvis.settings new file mode 100644 index 0000000..a2c8d9d --- /dev/null +++ b/settings/cuvis.settings @@ -0,0 +1,135 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/settings/system.settings b/settings/system.settings new file mode 100644 index 0000000..96d0fe9 --- /dev/null +++ b/settings/system.settings @@ -0,0 +1,13 @@ + + + + + + + + + + + + + diff --git a/settings/ultris20.settings b/settings/ultris20.settings new file mode 100644 index 0000000..7324e7f --- /dev/null +++ b/settings/ultris20.settings @@ -0,0 +1,20 @@ + + + + + + + + + + + + + + + + + + + + diff --git a/settings/ultris20plus.settings b/settings/ultris20plus.settings new file mode 100644 index 0000000..292f7f7 --- /dev/null +++ b/settings/ultris20plus.settings @@ -0,0 +1,26 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/settings/ultris5.settings b/settings/ultris5.settings new file mode 100644 index 0000000..cdd1b5a --- /dev/null +++ b/settings/ultris5.settings @@ -0,0 +1,30 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + From 019f16d0da30f23f904d18eecfd84d07ec1ba698 Mon Sep 17 00:00:00 2001 From: Philip Manke Date: Fri, 5 Sep 2025 12:14:08 +0200 Subject: [PATCH 04/11] Fix typo --- Example_5_Record_Video.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Example_5_Record_Video.ipynb b/Example_5_Record_Video.ipynb index 3f7c743..efd0725 100644 --- a/Example_5_Record_Video.ipynb +++ b/Example_5_Record_Video.ipynb @@ -210,7 +210,7 @@ "The *Worker* is a class that implements a processing and/or recording pipeline.\n", "It manages the acquisition of measurements from the *AcquisitionContext* and manages handing them to further processing and/or exporting steps as you define them.\n", "This allows your application code to avoid dealing with asynchronous processing and resource management (compute, threads).\n", - "Using settings files and paramters in its constructor, you can define some characteristics of the *Worker*, eg. how many threads it will occupy at maximum.\n", + "Using settings files and parameters in its constructor, you can define some characteristics of the *Worker*, eg. how many threads it will occupy at maximum.\n", "\n", "A typical *Worker* setup looks like this:\n", "\n", From 55a367415adae32bf47fb2b9de9651b4b30897e2 Mon Sep 17 00:00:00 2001 From: Philip Manke Date: Thu, 11 Sep 2025 14:39:54 +0200 Subject: [PATCH 05/11] Fix typo --- Example_1_Take_Snapshot.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Example_1_Take_Snapshot.ipynb b/Example_1_Take_Snapshot.ipynb index 62dc164..f5de42b 100644 --- a/Example_1_Take_Snapshot.ipynb +++ b/Example_1_Take_Snapshot.ipynb @@ -162,7 +162,7 @@ "\n", "# Set camera to software trigger\n", "acq.operation_mode = cuvis.OperationMode.Software\n", - "acq.integration_time = snapshot_integration_time" + "acq.integration_time = snapshot_integration_time_ms" ] }, { From 3c0702ec10e8a6974613becce08fea09d13d7d35 Mon Sep 17 00:00:00 2001 From: Nima Ghorbani Date: Tue, 7 Oct 2025 14:47:47 +0200 Subject: [PATCH 06/11] Add interactive tools to load measurement notebook --- Example_2_Load_Measurement.ipynb | 414 +++++++++++++++++++++++++++++-- 1 file changed, 393 insertions(+), 21 deletions(-) diff --git a/Example_2_Load_Measurement.ipynb b/Example_2_Load_Measurement.ipynb index af713b3..a3bf237 100644 --- a/Example_2_Load_Measurement.ipynb +++ b/Example_2_Load_Measurement.ipynb @@ -30,14 +30,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "5b90c64f-97c1-4161-9663-24842475a747", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cuvis Python SDK Example 2\n", + "Initializing Cuvis\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\nima.ghorbani\\code-repos\\cuvis.python.examples\\.venv\\Lib\\site-packages\\cuvis\\General.py:4: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + } + ], "source": [ "# If the import of cuvis fails, the most common cause is a mismatch between\n", "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", "# Try re-installing both and make sure that the version numbers match exactly\n", + "%matplotlib widget\n", + "\n", "import cuvis\n", "import time\n", "from matplotlib import pyplot as plt\n", @@ -72,10 +91,20 @@ "execution_count": null, "id": "b09c072a-9665-4398-a2bd-9563814a275f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading Session File './SDK_Training_Example_Data/WinterUlm_X20P.cu3s'\n" + ] + } + ], "source": [ "# Enter a path applicable to your setup here\n", + "import os\n", "session_file_path = \"./SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", + "assert os.path.exists(demo_session_file), f\"Demo session file not found: {demo_session_file}\"\n", "\n", "# Load the SessionFile\n", "print(F\"Loading Session File '{session_file_path}'\")\n", @@ -84,10 +113,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "b3972f90-efea-4a9c-8301-b30274482ef7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Session File './SDK_Training_Example_Data/WinterUlm_X20P.cu3s' meta-data:\n", + "Number of measurements: 31\n", + "Recorded with operation mode: Software / Snapshot\n", + "Session File stores 4 reference measurements\n" + ] + } + ], "source": [ "# Read and output some session file meta-data\n", "print(F\"Session File '{session_file_path}' meta-data:\")\n", @@ -96,6 +136,7 @@ "\n", "print(\"Recorded with operation mode: \", end=\"\")\n", "recording_mode = session.operation_mode\n", + "\n", "if recording_mode == cuvis.OperationMode.Software:\n", " print(\"Software / Snapshot\")\n", "elif recording_mode == cuvis.OperationMode.Internal:\n", @@ -131,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "17152989-8f61-4c43-810c-9651bc6bc9ca", "metadata": {}, "outputs": [], @@ -142,10 +183,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "c6f1d9ac-6b4f-4db6-847f-33ade9f79e5d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement meta-data for measurement winter_ulm_000_0050:\n", + "Captured at: 2025-01-20 09:27:34.821000\n", + "Captured with exposure / integration time of: 7.0 ms\n", + "Captured with camera: Ultris X20P - BX20P221704\n", + "Captured with software version: 3.3.0 build: c9537bec41c2184bf68c9dcf05baea7aac3b9409 flags: RELEASE GPU_CUDA platform: win32 architecture: 64 Bit\n", + "Captured to: SDK_Training_Example_Data\\WinterUlm_X20P.cu3s\n" + ] + } + ], "source": [ "# Read and print some meta-data from the measurement\n", "print(F\"Measurement meta-data for measurement {measurement.name}:\")\n", @@ -159,10 +213,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "a550f1cf-a830-481f-9167-c85f98857da2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sensor pixel format: Mono12Packed\n", + "Sensor readout timestamp: 2025-01-20 09:27:34.821000\n", + "Sensor gain value: 1.1\n", + "Raw sensor size (WxH): (5120, 3840) pixel\n", + "Sensor temperature: 19.0 °C\n" + ] + } + ], "source": [ "# Access some meta-data from the sensor of the camera at the time of recording.\n", "# The raw sensor image of the hyperspectral sensor is called \"IMAGE\" by convention.\n", @@ -178,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "f684b471-3486-4842-80b5-a55e6b5c8629", "metadata": {}, "outputs": [], @@ -193,15 +259,34 @@ " pc.processing_mode = cuvis.ProcessingMode.Raw\n", " pc.apply(measurement)\n", "\n", - "cube = measurement.cube" + "cube = measurement.cube\n", + "#Or dummy random data for testing without cuvis package:\n", + "# class Cube:\n", + "# def __init__(self, h, w, c):\n", + "# self.height = h\n", + "# self.width = w\n", + "# self.channels = c\n", + "# self.array = np.random.rand(h, w, c) * 100\n", + "# self.wavelength = np.linspace(400, 700, c)\n", + "# cube = Cube(50, 50, 20)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "41fbf383-305c-48c3-922a-b929dcbd4350", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cube wavelength range: 350nm to 1002nm\n", + "Cube spatial resolution (WxH): (410, 410) pixel\n", + "Cube spectral resolution: 164 channels @ ~4.0nm per channel\n" + ] + } + ], "source": [ "# Access some fundamental information about the cube\n", "print(F\"Cube wavelength range: {cube.wavelength[0]}nm to {cube.wavelength[-1]}nm\")\n", @@ -211,10 +296,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "912bafa6-dc2c-4a48-a0fe-6b81ab3d7b33", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "420b30f57185431bb69ececee8972be4", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Interactive pixel spectrum viewer\n", + "\n", + "fig, (ax_img, ax_spec) = plt.subplots(1, 2, figsize=(10, 5))\n", + "\n", + "# Start with middle channel image\n", + "mid_channel = cube.channels // 2\n", + "im = ax_img.imshow(cube.array[:, :, mid_channel], cmap='gray')\n", + "ax_img.set_title(f\"Click a pixel to see its spectrum (channel {mid_channel})\")\n", + "\n", + "# Empty plot for spectrum\n", + "(line,) = ax_spec.plot([], [], lw=1.5)\n", + "ax_spec.set_xlabel(\"Wavelength\")\n", + "ax_spec.set_ylabel(\"Counts\")\n", + "ax_spec.set_title(\"Spectrum\")\n", + "ax_spec.grid(True, alpha=0.3)\n", + "\n", + "# Click event handler\n", + "def onclick(event):\n", + " if event.inaxes == ax_img:\n", + " x = int(event.xdata)\n", + " y = int(event.ydata)\n", + " spectrum = cube.array[y, x, :]\n", + " line.set_data(cube.wavelength, spectrum)\n", + " ax_spec.relim()\n", + " ax_spec.autoscale_view()\n", + " ax_spec.set_title(f\"Spectrum at (x={x}, y={y})\")\n", + " fig.canvas.draw_idle()\n", + "\n", + "# Connect click event\n", + "fig.canvas.mpl_connect('button_press_event', onclick)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, "id": "23f26a05-3214-4af2-adf6-da60e5ee8155", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9aec03471a63446096f053755bff1fa8", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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_dom_classes=('widget-interact…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import ipywidgets as widgets\n", + "from ipywidgets import interact\n", + "import numpy as np\n", + "\n", + "def show_channel(c):\n", + " channel_image = cube.array[:, :, c]\n", + " fig = plt.figure(figsize=(5, 5))\n", + " fig.canvas.header_visible = False\n", + "\n", + " im = plt.imshow(channel_image, cmap=\"gray\")\n", + " plt.title(f\"Channel {c}\")\n", + " plt.colorbar(im, fraction=0.046, pad=0.04)\n", + " plt.show()\n", + "\n", + "# Create an interactive slider for channel index\n", + "interact(show_channel, c=widgets.IntSlider(min=0, max=cube.channels - 1, step=1, value=cube.channels // 2));\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "2d633357", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "319a529358934278909c35c35f498bbc", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "IntSlider(value=82, description='Channel', max=163)" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "93db7ac1e923415ca0227f4f4af10328", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " Figure\n", + "
\n", + " \n", + "
\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# The full interactive viewer with channel slider and pixel spectrum on click\n", + "\n", + "fig, (ax_img, ax_spec) = plt.subplots(1, 2, figsize=(10, 5))\n", + "\n", + "plt.tight_layout()\n", + "\n", + "mid_channel = cube.channels // 2\n", + "im = ax_img.imshow(cube.array[:, :, mid_channel], cmap='gray')\n", + "marker, = ax_img.plot([], [], \"r+\", markersize=10, markeredgewidth=2)\n", + "ax_img.set_title(f\"Channel {mid_channel}\")\n", + "\n", + "(line,) = ax_spec.plot([], [], lw=1.5)\n", + "vline = ax_spec.axvline(cube.wavelength[mid_channel], color=\"r\", ls=\"--\", lw=1)\n", + "ax_spec.set_xlabel(\"Wavelength\")\n", + "ax_spec.set_ylabel(\"Counts\")\n", + "ax_spec.set_title(\"Spectrum\")\n", + "ax_spec.grid(True, alpha=0.3)\n", + "\n", + "selected_pixel = {\"x\": None, \"y\": None}\n", + "\n", + "# --- Channel slider setup (define before callbacks) ---\n", + "channel_slider = widgets.IntSlider(\n", + " value=mid_channel,\n", + " min=0,\n", + " max=cube.channels - 1,\n", + " step=1,\n", + " description=\"Channel\",\n", + " continuous_update=True,\n", + ")\n", + "\n", + "# --- Click handler ---\n", + "def onclick(event):\n", + " if event.inaxes == ax_img and event.xdata is not None and event.ydata is not None:\n", + " x, y = int(event.xdata), int(event.ydata)\n", + " if 0 <= x < cube.array.shape[1] and 0 <= y < cube.array.shape[0]:\n", + " selected_pixel[\"x\"], selected_pixel[\"y\"] = x, y\n", + " marker.set_data([x], [y])\n", + " \n", + " spectrum = np.array(cube.array[y, x, :]).ravel()\n", + " wavelengths = np.array(cube.wavelength).ravel()\n", + " line.set_data(wavelengths, spectrum)\n", + "\n", + " ax_spec.relim()\n", + " ax_spec.autoscale_view()\n", + " ch = channel_slider.value\n", + " vline.set_xdata([cube.wavelength[ch]])\n", + " ax_spec.set_title(\n", + " f\"Spectrum at (x={x}, y={y}) — value={cube.array[y, x, ch]:.3f}\"\n", + " )\n", + " fig.canvas.draw_idle()\n", + "\n", + "\n", + "fig.canvas.mpl_connect(\"button_press_event\", onclick)\n", + "\n", + "# --- Slider handler ---\n", + "def on_channel_change(change):\n", + " if change[\"name\"] == \"value\":\n", + " ch = change[\"new\"]\n", + " im.set_data(cube.array[:, :, ch])\n", + " ax_img.set_title(f\"Channel {ch}\")\n", + " vline.set_xdata(cube.wavelength[ch])\n", + " # keep marker visible even when no click yet\n", + " if selected_pixel[\"x\"] is not None:\n", + " x, y = selected_pixel[\"x\"], selected_pixel[\"y\"]\n", + " marker.set_data([x], [y]) \n", + " ax_spec.set_title(\n", + " f\"Spectrum at (x={x}, y={y}) — value={cube.array[y, x, ch]:.3f}\"\n", + " )\n", + " else:\n", + " marker.set_data([], []) \n", + " fig.canvas.draw_idle()\n", + "\n", + "channel_slider.observe(on_channel_change, names=\"value\")\n", + "\n", + "display(channel_slider)\n", + "plt.show()\n" + ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": ".venv (3.12.7)", "language": "python", "name": "python3" }, @@ -265,7 +637,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.7" } }, "nbformat": 4, From 87ad97fc24ef455a50352ffa424a1b166fa92bd2 Mon Sep 17 00:00:00 2001 From: Nima Ghorbani Date: Tue, 7 Oct 2025 15:41:18 +0200 Subject: [PATCH 07/11] set has_camera flag to example 1 --- .gitignore | 7 +- Example_1_Take_Snapshot.ipynb | 125 +++++++++++++++++++++-------- SDK_Training_Example_Data/.gitkeep | 0 3 files changed, 99 insertions(+), 33 deletions(-) create mode 100644 SDK_Training_Example_Data/.gitkeep diff --git a/.gitignore b/.gitignore index 90633df..de0f003 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,9 @@ /.venv /.venv39 /exit -*.log \ No newline at end of file +*.log +*.cu3s +.history/* +output/ +save/ +.ipynb_checkpoints/ \ No newline at end of file diff --git a/Example_1_Take_Snapshot.ipynb b/Example_1_Take_Snapshot.ipynb index f5de42b..cbd33a8 100644 --- a/Example_1_Take_Snapshot.ipynb +++ b/Example_1_Take_Snapshot.ipynb @@ -34,13 +34,31 @@ "execution_count": null, "id": "b3391452-d716-4fb2-8977-fa95b09b54ff", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cuvis Python SDK Example 1\n", + "Initializing Cuvis\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\nima.ghorbani\\code-repos\\cuvis.python.examples\\.venv\\Lib\\site-packages\\cuvis\\General.py:4: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + } + ], "source": [ "# If the import of cuvis fails, the most common cause is a mismatch between\n", "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", "# Try re-installing both and make sure that the version numbers match exactly\n", "import cuvis\n", "import time\n", + "\n", "print(\"Cuvis Python SDK Example 1\")\n", "\n", "# Initialize the Cuvis SDK using a settings-directory\n", @@ -53,19 +71,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "d345b826-29ba-4090-a7fa-4a016bd62905", "metadata": {}, "outputs": [], "source": [ "# Snapshot setup / User input\n", "# Enter your data here!\n", + "import os\n", + "\n", "snapshot_integration_time_ms = 100\n", - "save_directory = \"./directory to save the measurements to here\"\n", + "save_directory = \"./output\" # set to a location where you want to save the data\n", + "\n", + "has_camera = False # Set to True if you have a camera connected\n", "camera_serial_number_str = \"Your camera serial here\"\n", "\n", "# If using demo data instead of a physical camera, change this to your download location:\n", - "demo_session_file = \"/SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", + "demo_session_file = \"./SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", + "assert os.path.exists(demo_session_file), f\"Demo session file not found: {demo_session_file}\"\n", "\n", "camera_calibration_file_path = F\"./factory/{camera_serial_number_str}.cu3c\"" ] @@ -88,14 +111,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "34fdcae0-4b4b-49a3-b426-8bfa78f3d716", "metadata": {}, "outputs": [], "source": [ "# Skip this if working without a physical camera\n", - "print(\"Load camera calibration file\")\n", - "calib = cuvis.SessionFile(camera_calibration_file_path)" + "if has_camera:\n", + " print(\"Load camera calibration file\")\n", + " calib = cuvis.SessionFile(camera_calibration_file_path)" ] }, { @@ -112,10 +136,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "05024d39-f138-42c7-abdc-9cd0a5c5b581", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Create CubeExporter\n" + ] + } + ], "source": [ "# Setup the Cube Exporter for saving the measurements to disk in the SessionFile format (.cu3s)\n", "print(\"Create CubeExporter\")\n", @@ -144,25 +176,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "b47e7223-b588-4b4d-8059-f15b44c8cfb2", "metadata": {}, "outputs": [], "source": [ "# Skip this if working without a physical camera\n", - "print(\"Loading Acquisition Context\")\n", - "acq = cuvis.AcquisitionContext(calib)\n", + "if has_camera:\n", + " # Create an AcquisitionContext to connect to the camera\n", + " print(\"Loading Acquisition Context\")\n", + " acq = cuvis.AcquisitionContext(calib)\n", "\n", - "# Wait for camera connection to be established\n", - "print(\"Connecting with camera\")\n", - "while(not acq.ready):\n", - " time.sleep(1)\n", - " print(\".\", end=\"\")\n", - "print(\"\\nCamera connected!\")\n", + " # Wait for camera connection to be established\n", + " print(\"Connecting with camera\")\n", + " while(not acq.ready):\n", + " time.sleep(1)\n", + " print(\".\", end=\"\")\n", + " print(\"\\nCamera connected!\")\n", "\n", - "# Set camera to software trigger\n", - "acq.operation_mode = cuvis.OperationMode.Software\n", - "acq.integration_time = snapshot_integration_time_ms" + " # Set camera to software trigger\n", + " acq.operation_mode = cuvis.OperationMode.Software\n", + " acq.integration_time = snapshot_integration_time_ms" ] }, { @@ -181,15 +215,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "4080c54c-6341-4257-bbd4-d555372d8798", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wait for Acqusition Context to be ready...\n", + "\n", + "Simulated camera loaded!\n" + ] + } + ], "source": [ "# Simulated Acquisition: Skip this if working with a physical camera\n", - "session = cuvis.SessionFile(demo_session_file)\n", - "# Initialize the Acquisition Context in simulated camera mode\n", - "acq = cuvis.AcquisitionContext(session, simulate=True)\n", + "if not has_camera:\n", + " session = cuvis.SessionFile(demo_session_file)\n", + " # Initialize the Acquisition Context in simulated camera mode\n", + " acq = cuvis.AcquisitionContext(session, simulate=True)\n", "\n", "# Wait for the Acquisition Context to load the demo session file\n", "print(\"Wait for Acqusition Context to be ready...\")\n", @@ -215,10 +260,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "99a6438c-70b7-4403-9b61-44385ff32a0e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement reports: AsyncResult.done\n" + ] + } + ], "source": [ "# Optional: Name the recording\n", "acq.session_info = cuvis.SessionData(\"My_Measurement\", 0, 0)\n", @@ -234,10 +287,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "7e6633d5-b1ed-4570-a1b6-5ed1b2dec105", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement exported!\n" + ] + } + ], "source": [ "# Export the measurement - write the data to the disk in SessionFile format using the CubeExporter\n", "if status == cuvis.Async.AsyncResult.done:\n", @@ -250,7 +311,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": ".venv (3.12.7)", "language": "python", "name": "python3" }, @@ -264,7 +325,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/SDK_Training_Example_Data/.gitkeep b/SDK_Training_Example_Data/.gitkeep new file mode 100644 index 0000000..e69de29 From cfbe445a42213cb65a9a295923cd5092135daf9f Mon Sep 17 00:00:00 2001 From: Nima Ghorbani Date: Tue, 7 Oct 2025 15:42:48 +0200 Subject: [PATCH 08/11] Add example measurement, and dark and white references and an interactive viewer --- Example_2_Load_Measurement.ipynb | 2 +- Example_3_Reprocess.ipynb | 425 +++++++++++++++++++++++++++++-- settings/cuvis.settings | 4 +- 3 files changed, 403 insertions(+), 28 deletions(-) diff --git a/Example_2_Load_Measurement.ipynb b/Example_2_Load_Measurement.ipynb index a3bf237..af6ecf9 100644 --- a/Example_2_Load_Measurement.ipynb +++ b/Example_2_Load_Measurement.ipynb @@ -88,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "b09c072a-9665-4398-a2bd-9563814a275f", "metadata": {}, "outputs": [ diff --git a/Example_3_Reprocess.ipynb b/Example_3_Reprocess.ipynb index a3c568e..0c7e39a 100644 --- a/Example_3_Reprocess.ipynb +++ b/Example_3_Reprocess.ipynb @@ -32,10 +32,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "ece811fb-7ad0-4dfe-b2f9-586341f1610f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\nima.ghorbani\\code-repos\\cuvis.python.examples\\.venv\\Lib\\site-packages\\cuvis\\General.py:4: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cuvis Python SDK Example 3\n", + "Initializing Cuvis\n" + ] + } + ], "source": [ "# If the import of cuvis fails, the most common cause is a mismatch between\n", "# the _cuvis_ python package and the installed version of the Cuvis SDK.\n", @@ -56,15 +73,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "cf42d3ed-9fd1-4170-9802-cb009cbecf81", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading Session File './SDK_Training_Example_Data/WinterUlm_X20P.cu3s'\n", + "Loading Dark reference file './SDK_Training_Example_Data/WinterUlm_X20P.cu3s'\n", + "Using Dark reference from Session File\n", + "Loading White reference file './SDK_Training_Example_Data/WinterUlm_X20P.cu3s'\n", + "Using White reference from Session File\n" + ] + } + ], "source": [ "# Enter paths applicable to your setup here\n", - "session_file_path = \"path/to/measurement.cu3s\"\n", - "dark_reference_file_path = \"path/to/reference measurement.cu3s\"\n", - "white_reference_file_path = \"path/to/reference measurement.cu3s\"\n", + "session_file_path = \"./SDK_Training_Example_Data/WinterUlm_X20P.cu3s\"\n", + "dark_reference_file_path = session_file_path #\"path/to/reference measurement.cu3s\"\n", + "white_reference_file_path = session_file_path #\"path/to/reference measurement.cu3s\"\n", "\n", "# Load the SessionFile\n", "print(F\"Loading Session File '{session_file_path}'\")\n", @@ -93,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "4379cbf0-5cb1-47ef-aa42-560ff3e53fa2", "metadata": {}, "outputs": [], @@ -118,6 +147,8 @@ "\n", "def show_spectrum_and_channel(measurement, i_x=None, i_y=None, i_c=None):\n", " cube = measurement.cube\n", + " print(F\"Cube dimensions: {cube.width} x {cube.height} x {cube.channels}\")\n", + " \n", " x = (cube.width // 2) if i_x is None else i_x\n", " y = (cube.height // 2) if i_y is None else i_y\n", " c = (cube.channels // 2) if i_c is None else i_c\n", @@ -160,10 +191,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "25d04ffd-104e-445b-b29b-422f1954a561", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement does not have a hyperspectral cube: Preview Mode\n" + ] + } + ], "source": [ "print_processing_mode(measurement)" ] @@ -188,12 +227,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "963f957f-d17c-40e6-aa35-eed218de4c51", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing mode is ProcessingMode.Raw\n" + ] + } + ], "source": [ - "processing_context = cuvis.ProcessingContext(session)" + "processing_context = cuvis.ProcessingContext(session)\n", + "print(\"Processing mode is\", processing_context.processing_mode)" ] }, { @@ -211,10 +259,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "ea4bcf06-391a-4cfe-92ec-cef635a99fa4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement has a hyperspectral cube with raw counts: Raw Mode\n", + "Cube dimensions: 410 x 410 x 164\n" + ] + }, + { + "data": { + "text/plain": [ + "(
,\n", + " (,\n", + " ))" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set processing mode\n", "processing_context.processing_mode = cuvis.ProcessingMode.Raw\n", @@ -241,10 +320,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "698ede88-f0ad-4274-8d56-d73338fda2bd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement has a hyperspectral cube with raw counts: Dark Subtract Mode\n", + "Cube dimensions: 410 x 410 x 164\n" + ] + }, + { + "data": { + "text/plain": [ + "(
,\n", + " (,\n", + " ))" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set processing mode\n", "processing_context.processing_mode = cuvis.ProcessingMode.DarkSubtract\n", @@ -281,10 +391,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "583d9592-8db3-4e49-96ce-f6d25ce57ffe", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement has a hyperspectral cube with reflectance values: Reflectance Mode\n", + "Cube dimensions: 410 x 410 x 164\n" + ] + }, + { + "data": { + "text/plain": [ + "(
,\n", + " (,\n", + " ))" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set processing mode\n", "processing_context.processing_mode = cuvis.ProcessingMode.Reflectance\n", @@ -320,10 +461,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "2ef2f20c-c456-4284-8f14-23faf79a2085", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Measurement has a hyperspectral cube with Spectral Radiance values: Spectral Radiance Mode\n", + "Cube dimensions: 410 x 410 x 164\n" + ] + }, + { + "data": { + "text/plain": [ + "(
,\n", + " (,\n", + " ))" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set processing mode\n", "processing_context.processing_mode = cuvis.ProcessingMode.SpectralRadiance\n", @@ -356,10 +528,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "e5924d2f-a6b3-44fb-9027-5cfcf93b7c37", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'With Distance')" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set processing mode\n", "processing_context.processing_mode = cuvis.ProcessingMode.Reflectance\n", @@ -392,11 +585,193 @@ "ax1.imshow(view_withdistance.array)\n", "ax1.set_title(\"With Distance\")" ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "b945df88", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f86ec29c81bd47769f5d2a0c6733b22f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Dropdown(description='Mode:', index=2, options=(('Preview', ), ('Raw', \n", + "
\n", + " Figure\n", + "
\n", + " \n", + " \n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Interactive visualization of different processing modes\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import ipywidgets as widgets\n", + "from IPython.display import display, clear_output\n", + "%matplotlib widget \n", + "\n", + "pc = processing_context\n", + "# --- Dropdown for selecting processing mode ---\n", + "mode_dropdown = widgets.Dropdown(\n", + " options=[\n", + " (\"Preview\", cuvis.ProcessingMode.Preview),\n", + " (\"Raw\", cuvis.ProcessingMode.Raw),\n", + " (\"DarkSubtract\", cuvis.ProcessingMode.DarkSubtract),\n", + " (\"Reflectance\", cuvis.ProcessingMode.Reflectance),\n", + " (\"SpectralRadiance\", cuvis.ProcessingMode.SpectralRadiance),\n", + " ],\n", + " value=cuvis.ProcessingMode.Raw,\n", + " description=\"Mode:\",\n", + ")\n", + "\n", + "# --- Processing and plotting function ---\n", + "def process_and_plot(change=None):\n", + " clear_output(wait=True)\n", + " display(mode_dropdown)\n", + "\n", + " # Set processing mode from dropdown\n", + " pc.processing_mode = mode_dropdown.value\n", + " pc.apply(measurement)\n", + " cube = measurement.cube\n", + "\n", + " # --- Plot setup ---\n", + " fig, (ax_img, ax_spec) = plt.subplots(1, 2, figsize=(10, 5))\n", + " plt.tight_layout()\n", + "\n", + " mid_channel = cube.channels // 2\n", + " im = ax_img.imshow(cube.array[:, :, mid_channel], cmap=\"gray\")\n", + " marker, = ax_img.plot([], [], \"r+\", markersize=10, markeredgewidth=2)\n", + " ax_img.set_title(f\"Channel {mid_channel}\")\n", + "\n", + " (line,) = ax_spec.plot([], [], lw=1.5)\n", + " vline = ax_spec.axvline(cube.wavelength[mid_channel], color=\"r\", ls=\"--\", lw=1)\n", + " ax_spec.set_xlabel(\"Wavelength\")\n", + " ax_spec.set_ylabel(\"Counts\")\n", + " ax_spec.set_title(\"Spectrum\")\n", + " ax_spec.grid(True, alpha=0.3)\n", + "\n", + " selected_pixel = {\"x\": None, \"y\": None}\n", + "\n", + " # --- Channel slider ---\n", + " channel_slider = widgets.IntSlider(\n", + " value=mid_channel,\n", + " min=0,\n", + " max=cube.channels - 1,\n", + " step=1,\n", + " description=\"Channel\",\n", + " continuous_update=True,\n", + " )\n", + "\n", + " # --- Click handler ---\n", + " def onclick(event):\n", + " if event.inaxes == ax_img and event.xdata is not None and event.ydata is not None:\n", + " x, y = int(event.xdata), int(event.ydata)\n", + " if 0 <= x < cube.array.shape[1] and 0 <= y < cube.array.shape[0]:\n", + " selected_pixel[\"x\"], selected_pixel[\"y\"] = x, y\n", + " marker.set_data([x], [y])\n", + "\n", + " spectrum = np.array(cube.array[y, x, :]).ravel()\n", + " wavelengths = np.array(cube.wavelength).ravel()\n", + " line.set_data(wavelengths, spectrum)\n", + "\n", + " ax_spec.relim()\n", + " ax_spec.autoscale_view()\n", + " ch = channel_slider.value\n", + " vline.set_xdata([cube.wavelength[ch]])\n", + " ax_spec.set_title(\n", + " f\"Spectrum at (x={x}, y={y}) — value={cube.array[y, x, ch]:.3f}\"\n", + " )\n", + " fig.canvas.draw_idle()\n", + "\n", + " fig.canvas.mpl_connect(\"button_press_event\", onclick)\n", + "\n", + " # --- Slider handler ---\n", + " def on_channel_change(change):\n", + " if change[\"name\"] == \"value\":\n", + " ch = change[\"new\"]\n", + " im.set_data(cube.array[:, :, ch])\n", + " ax_img.set_title(f\"Channel {ch}\")\n", + " vline.set_xdata([cube.wavelength[ch]])\n", + "\n", + " if selected_pixel[\"x\"] is not None:\n", + " x, y = selected_pixel[\"x\"], selected_pixel[\"y\"]\n", + " marker.set_data([x], [y])\n", + " ax_spec.set_title(\n", + " f\"Spectrum at (x={x}, y={y}) — value={cube.array[y, x, ch]:.3f}\"\n", + " )\n", + " else:\n", + " marker.set_data([], [])\n", + " fig.canvas.draw_idle()\n", + "\n", + " channel_slider.observe(on_channel_change, names=\"value\")\n", + "\n", + " display(channel_slider)\n", + " plt.show()\n", + "\n", + "# --- Link dropdown to processing ---\n", + "mode_dropdown.observe(process_and_plot, names=\"value\")\n", + "\n", + "# Display the dropdown for the first time\n", + "display(mode_dropdown)\n", + "process_and_plot()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f27b5e48", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": ".venv (3.12.7)", "language": "python", "name": "python3" }, @@ -410,7 +785,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.7" } }, "nbformat": 4, diff --git a/settings/cuvis.settings b/settings/cuvis.settings index a2c8d9d..67e1c15 100644 --- a/settings/cuvis.settings +++ b/settings/cuvis.settings @@ -37,9 +37,9 @@ - + - +