import PySimpleGUI as sg import cv2 import numpy as np """ Demo program that displays a webcam using OpenCV and applies some very basic image functions - functions from top to bottom - none: no processing threshold: simple b/w-threshold on the luma channel, slider sets the threshold value canny: edge finding with canny, sliders set the two threshold values for the function => edge sensitivity contour: colour finding in the frame, first slider sets the hue for the colour to find, second the minimum saturation for the object. Found objects are drawn with a red contour. blur: simple Gaussian blur, slider sets the sigma, i.e. the amount of blur smear hue: moves the image hue values by the amount selected on the slider enhance: applies local contrast enhancement on the luma channel to make the image fancier - slider controls fanciness. """ def main(): sg.theme('LightGreen') # define the window layout layout = [ [sg.Text('OpenCV Demo', size=(40, 1), justification='center')], [sg.Image(filename='', key='image')], [sg.Radio('None', 'Radio', True, size=(10, 1))], [sg.Radio('threshold', 'Radio', size=(10, 1), key='thresh'), sg.Slider((0, 255), 128, 1, orientation='h', size=(40, 15), key='thresh_slider')], [sg.Radio('canny', 'Radio', size=(10, 1), key='canny'), sg.Slider((0, 255), 128, 1, orientation='h', size=(20, 15), key='canny_slider_a'), sg.Slider((0, 255), 128, 1, orientation='h', size=(20, 15), key='canny_slider_b')], [sg.Radio('contour', 'Radio', size=(10, 1), key='contour'), sg.Slider((0, 255), 128, 1, orientation='h', size=(20, 15), key='contour_slider'), sg.Slider((0, 255), 80, 1, orientation='h', size=(20, 15), key='base_slider')], [sg.Radio('blur', 'Radio', size=(10, 1), key='blur'), sg.Slider((1, 11), 1, 1, orientation='h', size=(40, 15), key='blur_slider')], [sg.Radio('hue', 'Radio', size=(10, 1), key='hue'), sg.Slider((0, 225), 0, 1, orientation='h', size=(40, 15), key='hue_slider')], [sg.Radio('enhance', 'Radio', size=(10, 1), key='enhance'), sg.Slider((1, 255), 128, 1, orientation='h', size=(40, 15), key='enhance_slider')], [sg.Button('Exit', size=(10, 1))] ] # create the window and show it without the plot window = sg.Window('Demo Application - OpenCV Integration', layout, location=(800, 400), finalize=True) cap = cv2.VideoCapture(0) while True: event, values = window.read(timeout=0, timeout_key='timeout') if event == 'Exit' or event is None: break ret, frame = cap.read() if values['thresh']: frame = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB)[:, :, 0] frame = cv2.threshold(frame, values['thresh_slider'], 255, cv2.THRESH_BINARY)[1] if values['canny']: frame = cv2.Canny(frame, values['canny_slider_a'], values['canny_slider_b']) if values['blur']: frame = cv2.GaussianBlur(frame, (21, 21), values['blur_slider']) if values['hue']: frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) frame[:, :, 0] += values['hue_slider'] frame = cv2.cvtColor(frame, cv2.COLOR_HSV2BGR) if values['enhance']: enh_val = values['enhance_slider'] / 40 clahe = cv2.createCLAHE(clipLimit=enh_val, tileGridSize=(8, 8)) lab = cv2.cvtColor(frame, cv2.COLOR_BGR2LAB) lab[:, :, 0] = clahe.apply(lab[:, :, 0]) frame = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR) if values['contour']: hue = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) hue = cv2.GaussianBlur(hue, (21, 21), 1) hue = cv2.inRange(hue, np.array([values['contour_slider'], values['base_slider'], 40]), np.array([values['contour_slider'] + 30, 255, 220])) cnts = cv2.findContours(hue, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[1] cv2.drawContours(frame, cnts, -1, (0, 0, 255), 2) imgbytes = cv2.imencode('.png', frame)[1].tobytes() window['image'].update(data=imgbytes) window.close() main()