Create Demo_OpenCV_Simple_GUI.py

A simple example where different OpenCV functions can be controlled via PySimpleGUI in realtime. Is that going in the right direction?

Demo_OpenCV_Simple_GUI.py

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+import sys
+if sys.version_info[0] >= 3:
+  import PySimpleGUI as sg
+else:
+  import PySimpleGUI27 as sg
+import cv2
+import numpy as np
+from sys import exit as exit
+
+"""
+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.ChangeLookAndFeel('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.ReadButton('Exit', size=(10, 1))]]
+
+  # create the window and show it without the plot
+  window = sg.Window('Demo Application - OpenCV Integration',
+                     location=(800,400))
+  window.Layout(layout).Finalize()
+
+  cap = cv2.VideoCapture(0)
+  while True:
+    event, values = window.ReadNonBlocking()
+    if event == 'Exit' or values is None:
+      sys.exit(0)
+    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)
+    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)
+      cv2.drawContours(frame,cnts,-1,(0,0,255),2)
+    imgbytes=cv2.imencode('.png', frame)[1].tobytes() #ditto
+    window.FindElement('image').Update(data=imgbytes)
+
+main()