Booking.com Image Gathering and Integration into TraffickCam

This directory contains the code to gather data from every hotel in the United States from Booking.com. The data includes hotel name, gps coordinates, hotel address (including city, state, etc.), rating, and all the links to the hotel's images. The directory also contains code to download all the images from the links gathered onto the server. The ultimate goal of this project is to integrate all the images of booking.com hotels into the existing TraffickCam hotel image corpus.

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📂 Project Structure

Here's a quick breakdown of the repository contents:

File / Directory	Purpose
README.md	📄 Documentation for understanding and using this template.
.gitignore	🚫 Ensures that large files, logs, and unnecessary cache files are not committed to Git.
requirements.txt	📦 Lists all required dependencies (for pip install -r requirements.txt).
scripts/	🛠 Contains reusable Python scripts for preprocessing, training, and evaluation.
results/	📊 Stores logs, metrics, and experiment outputs.
data/	📁 Placeholder for datasets (already in .gitignore, so any datasets added here won’t be committed to Git).

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🚀 Getting Started

🔹 1. Clone the Repository

git clone https://github.com/deltalucas/booking-image-integration.git
cd booking-image-integration

🛠 Setting Up the Dataset (GPU Server)

To avoid hardcoding dataset paths, create a symbolic link inside data/ pointing to your dataset location:

ln -s /absolute/path/to/dataset /path/to/ml-project-template/data/dataset_name

Where You're Running the Notebook	Dataset Setup
GPU Server (Jupyter Notebook Server)	Use a symlink (ln -s) to point to the real dataset.
Local Machine (VS Code, Jupyter, etc.)	Create a small sample dataset inside data/.
Google Colab (Cloud)	Upload a sample dataset to Google Drive inside data/.