import numpy as np
import cv2

cap = cv2.VideoCapture('recordings/test1.webm')

ret, frame1 = cap.read()
ret, frame2 = cap.read()

while(cap.isOpened()):
    diff = cv2.absdiff(frame1, frame2)
    gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (5,5), 0)
    _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)
    dilated = cv2.dilate(thresh, None, iterations=3)
    contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        (x, y, w, h) = cv2.boundingRect(contour)

        if cv2.contourArea(contour) < 9000:
            continue
        cv2.rectangle(frame1, (x, y), (x+w, y+h), (0, 255, 0), 2)
        cv2.putText(frame1, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

    cv2.imshow("feed", frame1)
    frame1 = frame2
    ret, frame2 = cap.read()

    if cv2.waitKey(25) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()




# import numpy as np
# import cv2

# cap = cv2.VideoCapture('recordings/test1.webm')

# while(cap.isOpened()):
#     # Capture frame-by-frame
#     ret, frame = cap.read()

#     # Our operations on the frame come here
#     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

#     # Display the resulting frame
#     cv2.imshow('frame',gray)
#     if cv2.waitKey(25) & 0xFF == ord('q'):
#         break

# # When everything done, release the capture
# cap.release()
# cv2.destroyAllWindows()





# from imageai.Detection import VideoObjectDetection
# import os

# execution_path = os.getcwd()

# detector = VideoObjectDetection()
# detector.setModelTypeAsYOLOv3()
# detector.setModelPath( os.path.join(execution_path , "yolo.h5"))
# detector.loadModel()

# video_path = detector.detectObjectsFromVideo(input_file_path=os.path.join( execution_path, "recordings/traffic-mini.mp4"),
#                                 output_file_path=os.path.join(execution_path, "outputs/traffic_mini_detected_1")
#                                 , frames_per_second=29, log_progress=True)
# print(video_path)