video stream success with pi camera

detect.py

@@ -75,38 +75,45 @@ ap.add_argument("-n", "--number", type=int, required=False,
                     help="show on the screen")
     args = vars(ap.parse_args())
     args2 = ap.parse_args()"""
-def detect(calibration_width, img_file, show):
+def detect(calibration_width, img_file, show, quick):
     selected = 2
     #if type(args["number"]) == type(selected):
     #    selected = args["number"]
 
     # load the image, convert it to grayscale, and blur it slightly
-    image = cv2.imread(img_file)
+    image = None
+    print(str(type(img_file)))
+    if str(type(img_file)) == "<class 'numpy.ndarray'>":
+        image = img_file.copy()
+    else:
+        image = cv2.imread(img_file)
+    
+    #image = img_file.copy()
     #image = cv2.resize(image, (int(image.shape[1]*1), int(image.shape[0]*1)))
     image = cv2.resize(image, (1000, int(
         image.shape[0]/image.shape[1] * 1000)), interpolation=cv2.INTER_NEAREST)
 
-    if show:
+    if show and not quick:
         cv2.namedWindow("Item Sorter")
         cv2.imshow("Item Sorter", image)
         cv2.waitKey(0)
     gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     gray = cv2.GaussianBlur(gray, (5, 5), 0)
-    if show:
+    if show and not quick:
         cv2.imshow("Item Sorter", gray)
         cv2.waitKey(0)
 
     # perform edge detection, then perform a dilation + erosion to
     # close gaps in between object edges
     edged = cv2.Canny(gray, 50, 100)
-    if show:
+    if show and not quick:
         cv2.imshow("Item Sorter", edged)
         cv2.waitKey(0)
 
     edged = cv2.dilate(edged, None, iterations=1)
     edged = cv2.erode(edged, None, iterations=1)
 
-    if show:
+    if show and not quick:
         cv2.imshow("Item Sorter", edged)
         cv2.waitKey(0)
     # find contours in the edge map
@@ -171,7 +178,7 @@ def detect(calibration_width, img_file, show):
             pixelsPerMetric = smaller(dA, dB) / calibration_width
             continue
 
-
+    pixelsPerMetric = 25
     orig = image.copy()
     objtype = "Unknown"
     objname = ""
@@ -180,7 +187,7 @@ def detect(calibration_width, img_file, show):
         #orig = image.copy()
         num += 1
         # if the contour is not sufficiently large, ignore it
-        if cv2.contourArea(c) < 100 or pixelsPerMetric is None:
+        if cv2.contourArea(c) < 100: # or pixelsPerMetric is None:
             continue
         # compute the rotated bounding box of the contour
 
@@ -357,5 +364,7 @@ def detect(calibration_width, img_file, show):
                 if show:
                     cv2.imshow("Item Sorter", orig)
                 #cv2.waitKey(1)
-
+    if quick:
-    cv2.waitKey(0)
+        return orig
+    else:
+        cv2.waitKey(0)

run_detect.py

@@ -5,7 +5,7 @@ calibration_width = 0.75
 image = "img7.jpg"
 images = ("img.jpg", "img2.jpg", "img3.jpg", "img4.jpg", "img5.jpg", "img6.jpg", "img7.jpg", "img8.jpg")
 show = False
-video = False
+video = True
 def go():
     #for file in images:
     detect.detect(calibration_width, "img7.jpg", show)
@@ -14,14 +14,19 @@ if not video:
 	elapsed_time = timeit.timeit(go, number=3)/3
 	print(elapsed_time)
 else :
-    capture = cv2.VideoCapture('tcpclientsrc host=192.168.43.152 port=5000 ! queue ! decodebin ! appsink', cv2.CAP_GSTREAMER)
+    capture = cv2.VideoCapture('tcpclientsrc host=192.168.86.108 port=5001  ! gdpdepay !  rtph264depay ! avdec_h264 ! videoconvert ! appsink', cv2.CAP_GSTREAMER)
+    # server command for pi camera /opt/vc/bin/raspivid -t 0 -w 1920 -h 1080 -hf -fps 5 -o - | gst-launch-1.0 -v fdsrc ! h264parse !  rtph264pay config-interval=1 pt=96 ! gdppay ! tcpserversink host=192.168.86.108 port=5001
+    ret,frame = capture.read()
+    detect.detect(calibration_width, "img7.jpg", True, False)
+    detect.detect(calibration_width, frame, True, True)
     while True:
         ret,frame = capture.read()
 
         if not ret:
             print('empty frame')
             break
-        print('frame')
+        #print('frame')
-        cv2.imshow('receive', frame)
+        
+        cv2.imshow('Item Sorter', detect.detect(calibration_width, frame, True, True))
         if cv2.waitKey(1)&0xFF == ord('q'):
             break