.gitignore

@@ -4,6 +4,3 @@ venv/
 camera/venv
 camera/images
 camera/videos
-*.jpg
-*.h264
-*.mp4

camera/image_presence.py

@@ -49,7 +49,6 @@ for imagePath in paths.list_images(args["images"]):
     print("[INFO] {}: {} original boxes, {} after suppression".format(filename, len(rects), len(pick)))
 
     # show the output images
-    if len(pick):
     #cv2.imshow("Before NMS", orig)
-        cv2.imshow("After NMS", image)
-        cv2.waitKey(0)
+    #cv2.imshow("After NMS", image)
+    #cv2.waitKey(0)

camera/video_presence.py

@@ -50,7 +50,6 @@ if args.get("video", None) is None:
 # otherwise, we are reading from a video file
 else:
     vs = cv2.VideoCapture(args["video"])
-    #vs.set(cv2.CAP_PROP_FPS, 2)
 
 """" Analyzing video frames """
 # loop over the frames of the video, and store corresponding information from each frame
@@ -93,7 +92,7 @@ while True:
         # dilate the thresholded image to fill in holes, then find contours on thresholded image
         thresh = cv2.dilate(thresh, None, iterations=2)
         thresh = np.uint8(thresh)
-        _, cnts, im2  = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+        cnts, im2  = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
         #cnts = cnts if imutils.is_cv2() else im2
         #print(len(cnts))
         #if len(cnts) > 1:
@@ -121,7 +120,7 @@ while True:
 
             trackbox = frame[y:y+h, x:x+w]
             trackbox = cv2.resize(trackbox, (224, 224))
-            #cv2.imshow('image',trackbox)
+            cv2.imshow('image',trackbox)
             blob = cv2.dnn.blobFromImage(cv2.resize(trackbox, (300, 300)),0.007843, (300, 300), 127.5)
             net.setInput(blob)
             detections = net.forward()