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|
- import cv2
- import time
- import numpy as np
-
- cap = cv2.VideoCapture(1)
-
- def threshold_slow(image):
- h = image.shape[0]
- w = image.shape[1]
- for y in range(0, h):
- for x in range(0, w):
- if np.any(image[y, x] != 0):
- return True
-
- return False
-
- while True:
- ret, frame = cap.read()
- frame_org = frame
- frame = frame[100:300, 100:300]
- hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
- sensitivity = 40
- lower_white = np.array([0,0,255-sensitivity])
- upper_white = np.array([255,sensitivity,255])
- mask = cv2.inRange(hsv, lower_white, upper_white)
- res = cv2.bitwise_and(frame,frame, mask=mask)
-
- res = cv2.erode(res, None, iterations=2)
- res = cv2.dilate(res, None, iterations=4)
-
- mask = cv2.erode(mask, None, iterations=2)
- mask = cv2.dilate(mask, None, iterations=4)
-
- if threshold_slow(res):
- cv2.rectangle(frame_org, (100, 100), (300, 300), (255, 0, 0), 2)
-
- cv2.imshow('frame', frame)
- cv2.imshow('org', frame_org)
- cv2.imshow('mask', mask)
- cv2.imshow('res', res)
-
- k = cv2.waitKey(5) & 0xFF
- if k == ord('q'):
- break
-
- cap.release()
- cv2.destroyAllWindows()
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