Week 3. Improving the pre proccesing

Week 3. Pre-proccesing code

for video in os.listdir(folder_path): if video.endswith(“.MP4”): video_name = video video_path = folder_path + video img_index = 0 v += 1

    frames_path = folder_path + '/' + video_name + '_frames'
    os.makedirs(frames_path,exist_ok=True)

    cap = cv2.VideoCapture(video_path)
    os.chdir(frames_path)
    black_img = create_blank(w, h, rgb_color=black)


    if len(dataX) != 0:
        testX.append(dataX)

    dataX = []

    print('\nVideo #' + str(v) + '-----------' + str(video_name) + '\n')

    # List all the frames
    while (cap.isOpened()):

        ret, frame = cap.read()
        if ret == False:
            break

        ''' FRAME RESIZED '''
        frame = resize(frame, 120, 80)
        ''' FRAME RESIZED '''

        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        hsv = cv2.bitwise_not(hsv) # Inverted filter color

        # Threshold in HSV space
        lower = np.array([225, 0, 0]) # Orange
        #lower = np.array([0, 0, 160]) # Green Background
        #lower = np.array([0, 0, 160]) # Black background
        upper = np.array([255, 255, 255])

        # The black region in the mask has the value of 0
        mask = cv2.inRange(hsv, lower, upper)
        result = cv2.bitwise_and(frame, frame, mask = mask)

        # Gray scale
        gray_image = cv2.cvtColor(result, cv2.COLOR_BGR2GRAY)

        # Binary Mode
        ret,binary_gray = cv2.threshold(gray_image,100,255,cv2.THRESH_BINARY)

        kernel = np.ones((3,3), np.uint8)       # 3x3 matrix
        erosion_image = cv2.erode(binary_gray, kernel, iterations=1)

        kernel = np.ones((5,5), np.uint8)     # 10x10 matrix
        dilation_image = cv2.dilate(erosion_image, kernel, iterations=1)

        # calculate moments of binary image
        M = cv2.moments(dilation_image)
        previous_cX = cX

        if int((M["m10"]) != 0) or int((M["m10"]) != 0) or int((M["m10"]) != 0) or int((M["m10"]) != 0):

            cX = int(M["m10"] / M["m00"])
            cY = int(M["m01"] / M["m00"])

            data_temp_x = []
            data_temp_y = []

            if img_index <= max_number_frames:
                data_temp_x.append(np.array(cY))
                data_temp_x.append(np.array(cX))
                dataX.append(data_temp_x)

                cv2.circle(dilation_image, (cX, cY), 3, (0, 0, 0), -1)
                #cv2.putText(dilation_image, "here", (cX - 10, cY - 15),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 2)
                cv2.circle(frame, (cX, cY), 3, (0, 0, 0), -1)
                #cv2.putText(frame, "here", (cX - 10, cY - 15),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 2)

                if (cX >= previous_cX):
                    print ('Frame#' + str(img_index) + ' centroid ----- ' + str(cX) + ' ' + str(cY))
                    cv2.imwrite('HVS+GREY+BIN(ERODE+DILATE) ' + str(img_index) + '.png', dilation_image)
                    cv2.imwrite('ORIGINAL ' + str(img_index) + '.png', frame)
                    cv2.circle(black_img, (cX, cY), 1, (246, 209, 81), -1)
                    cv2.imwrite('Real_Trails.png', black_img)

Finnally the improving of the script for extracting frames and add the centroid to the ball was working properly with the new videos recorded and use 100 fps in the camera setting instead of 50 fps