71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
import cv2
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import time
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import pandas
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from datetime import datetime
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prev_frame = None
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times = []
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# df = pandas.DataFrame(columns=["start", "end"])
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video = cv2.VideoCapture(0)
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status_new = 0
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counter = 0
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low_red = (176, 132, 97)
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high_red = (209, 151, 114)
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face_cascade = cv2.CascadeClassifier("smile.xml")
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while True:
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status_new, status_old = 0, status_new
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check, frame = video.read()
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only_cat = cv2.inRange(frame, low_red, high_red)
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# cat_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray = cv2.GaussianBlur(gray, (21, 21), 0)
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if prev_frame is None:
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prev_frame = gray
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# continue
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delta_frame = cv2.absdiff(prev_frame, gray)
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prev_frame = gray
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thresh_delta = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
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thresh_frame = cv2.dilate(thresh_delta, None, iterations=2)
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(_,cnts,_) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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print(len(cnts))
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for contour in cnts:
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if cv2.contourArea(contour) < 1000:
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continue
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status_new, status_old = 1, status_new
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(x, y, w, h) = cv2.boundingRect(contour)
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# cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 3)
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# status_list.append(status)
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if status_new != status_old:
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times.append(datetime.now())
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cv2.imwrite('media/capture{}.png'.format(counter), frame)
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counter += 1
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# cv2.imshow("capt", gray)
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# cv2.imshow("delta", delta_frame)
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# cv2.imshow("threshold", thresh_frame)
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faces = face_cascade.detectMultiScale(gray,
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scaleFactor=1.1,
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minNeighbors=10)
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# for x, y, w, h in faces:
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# img = cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 3)
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# print(type(faces))
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# cv2.imshow("face_detector", img)
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cv2.imshow('cat', only_cat)
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cv2.imshow("rectangle", frame)
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key = cv2.waitKey(1)
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if key==ord('q'):
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break
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# print(times)
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#
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# for t in range(0, len(times), 2):
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# df = df.append({"start": times[t], "end": times[t+1]}, ignore_index=True)
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#
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# df.to_csv("times.csv")
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video.release()
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cv2.destroyAllWindows
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