56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
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import os
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import sys
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import time
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import numpy as np
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import cv2
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cap=cv2.VideoCapture(0)
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#cap=cv2.VideoCapture("chien.mp4")
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kernel_blur=5
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seuil=15
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surface=1000
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ret, originale=cap.read()
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originale=cv2.cvtColor(originale, cv2.COLOR_BGR2GRAY)
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originale=cv2.GaussianBlur(originale, (kernel_blur, kernel_blur), 0)
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kernel_dilate=np.ones((5, 5), np.uint8)
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while True:
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ret, frame=cap.read()
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gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray=cv2.GaussianBlur(gray, (kernel_blur, kernel_blur), 0)
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mask=cv2.absdiff(originale, gray)
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mask=cv2.threshold(mask, seuil, 255, cv2.THRESH_BINARY)[1]
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mask=cv2.dilate(mask, kernel_dilate, iterations=3)
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contours, nada=cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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frame_contour=frame.copy()
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for c in contours:
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cv2.drawContours(frame_contour, [c], 0, (0, 255, 0), 5)
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if cv2.contourArea(c)<surface:
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continue
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x, y, w, h=cv2.boundingRect(c)
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cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)
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originale=gray
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cv2.putText(frame, "[o|l]seuil: {:d} [p|m]blur: {:d} [i|k]surface: {:d}".format(seuil, kernel_blur, surface), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 255, 255), 2)
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cv2.imshow("frame", frame)
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cv2.imshow("contour", frame_contour)
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cv2.imshow("mask", mask)
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intrus=0
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key=cv2.waitKey(30)&0xFF
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if key==ord('q'):
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break
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if key==ord('p'):
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kernel_blur=min(43, kernel_blur+2)
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if key==ord('m'):
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kernel_blur=max(1, kernel_blur-2)
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if key==ord('i'):
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surface+=1000
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if key==ord('k'):
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surface=max(1000, surface-1000)
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if key==ord('o'):
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seuil=min(255, seuil+1)
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if key==ord('l'):
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seuil=max(1, seuil-1)
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cap.release()
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cv2.destroyAllWindows()
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