InteractiveProgramming/card_detect.py at master · isaacvandor/InteractiveProgramming · GitHub

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""" Experiment with card detection and filtering using OpenCV """
''' SoftDes MP4: Interactive Programming - Isaac Vandor & Raquel Dunoff '''
''' Open camera and show detected card'''

# Import necessary packages
import cv2
import numpy as np
import time
import os
import card_setup

# Define constants and initialize variables
def mainloop():
    # Camera settings
    IM_WIDTH = 1280
    IM_HEIGHT = 720
    FRAME_RATE = 10
    #suit_name  = "Hearts"
    #rank_name = "Queen"

    ## Define font to use
    font = cv2.FONT_HERSHEY_DUPLEX

    # Initialize camera object and video feed from the camera. Change integer to reflect internal webcam versus usb webcam.
    video_stream = cv2.VideoCapture(1)
    time.sleep(1) # Give the camera time to warm up

    # Load the train rank and suit images
    path = os.path.dirname(os.path.abspath(__file__))
    train_ranks = card_setup.load_ranks( path + '/card_imgs/')
    train_suits = card_setup.load_suits( path + '/card_imgs/')

    '''
    Grab frames from the video stream
    and process them to find and identify playing cards.
    '''

    cam_quit = 0 # Loop control variable

    # Begin capturing frames
    while cam_quit == 0:
        start = time.time()
        # Grab frame from video stream
        #image = videostream.read()
        ret, image = video_stream.read()

        # Pre-process camera image (gray, blur, and threshold it)
        pre_proc = card_setup.preprocess_image(image)

        # Find and sort the contours of all cards in the image (query cards)
        contours_sort, contour_is_card = card_setup.find_cards(pre_proc)

        # If there are no contours, do nothing
        if len(contours_sort) != 0:

            # Initialize a new "cards" list to assign the card objects w/ k as index.
            cards = []
            k = 0

            # For each contour detected:
            for i in range(len(contours_sort)):
                if (contour_is_card[i] == 1):

                    # Append card object and run preprocess_card func. to generate
                    # flattened image and isolate card suit and rank
                    cards.append(card_setup.preprocess_card(contours_sort[i],image))

                    # Find the best rank and suit match for the card.
                    cards[k].best_rank_match,cards[k].best_suit_match,cards[k].rank_diff,cards[k].suit_diff = card_setup.match_card(cards[k],train_ranks,train_suits)

                    # Draw center point and match result on the image.
                    image, rank_name, suit_name = card_setup.draw_results(image, cards[k])
                    #print(str(rank_name))
                    #print(str(suit_name))
                    k = k + 1
            # Draw card contours on image
            if (len(cards) != 0):
                temp_contours = []
                for i in range(len(cards)):
                    temp_contours.append(cards[i].contour)
                cv2.drawContours(image,temp_contours, -1, (0,0,0), 3)
                cv2.drawContours(image,temp_contours, -1, (255,150,20), 2)

        # Finally, display the image
        cv2.imshow("Playing Card Detector",image)

        while (time.time() - start < 5):
            cam_quit=1

        # Poll the keyboard. If 'q' is pressed, exit the program.
        key = cv2.waitKey(1) & 0xFF
        if key == ord("q"):
            cam_quit = 1


    # Close all windows and close the video feed.
    cv2.destroyAllWindows()
    return (rank_name, suit_name)