filter_images.py

import cv2
import numpy as np
from datetime import datetime

VIDEO = 'Videomaterial/WIN_20230414_13_41_55_Pro.mp4'
capture = cv2.VideoCapture(VIDEO)

last = None
frame = None
diff = None
window = 'Filter'

# Einstellungen
min_threshold = 30
max_threshold = 110
img_threshold = 100
line_threshold = 30

def overlay_imgs(base, top):
    topgray = cv2.cvtColor(top, cv2.COLOR_RGB2GRAY)

    _, mask = cv2.threshold(topgray, 10, 255, cv2.THRESH_BINARY)
    mask_inv = cv2.bitwise_not(mask)
    # Now black-out the area of overlay
    img1_bg = cv2.bitwise_and(base,base,mask = mask_inv)
    # Take only region of from logo image.
    img2_fg = cv2.bitwise_and(top,top,mask = mask)

    return cv2.add(img1_bg, img2_fg)

def filter_image(image):
    global min_threshold, max_threshold, line_threshold, result, window
    image = image.copy()
    # Use canny edge detection
    image = cv2.Canny(image, min_threshold, max_threshold)

    # kernel = np.ones((5,5),np.uint8)
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5,5))
    image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)

    lines = cv2.HoughLinesP(image, cv2.HOUGH_PROBABILISTIC, np.pi/360, line_threshold, minLineLength=10, maxLineGap=20)

    overlay = np.zeros((image.shape[0], image.shape[1], 3), np.uint8)

    if lines is not None:
        for line in lines:
            x1,y1,x2,y2 = line[0]
            pts = np.array([[x1, y1], [x2, y2]], np.int32)
            cv2.polylines(overlay, [pts], False, (255, 0, 0), thickness=3)

    return overlay

# def img_callback(val):
#     global img_threshold, result

#     img_threshold = val
#     if result is not None:
#         filter_image(result)

# def max_callback(val):
#     global max_threshold, result

#     max_threshold = val
#     if result is not None:
#         filter_image(result)

def line_callback(val):
    global line_threshold, frame, diff

    line_threshold = val
    if diff is not None:
        overlay = filter_image(diff)

        result = overlay_imgs(frame, overlay)
        cv2.imshow(window, result)


cv2.namedWindow(window, cv2.WINDOW_AUTOSIZE)
cv2.createTrackbar('Line Threshold: ', window, line_threshold, 100, line_callback)

while capture.isOpened():
    ret, frame = capture.read()
    if ret == True:
        frame = cv2.resize(frame, (1280, 720))

        filter = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
        
        #frame = frame[:,:,2] # Blue Channel
        filter = cv2.medianBlur(filter, 3)
        if last is not None:
            diff = cv2.absdiff(filter, last) # Difference
            overlay = filter_image(diff)

            result = overlay_imgs(frame, overlay)
            cv2.imshow(window, result)

        last = filter
    
        code = cv2.waitKey(33)
        if code & 0xFF == ord('s'):
            now = datetime.now()
            str = now.strftime("%d_%m_%Y_%H_%M_%S")
            cv2.imwrite(f'Filter/IMG_{str}.png', result)

        if code & 0xFF == ord('q'):
            break

    else:
        break

capture.release()

cv2.destroyAllWindows()