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