add differing methods for opencv ver 3/4

camera/counter_people.py

@@ -13,20 +13,8 @@ Usage:
 
 python peopleCounter.py -i PATH_TO_IMAGE  # Reads and detect people in a single local stored image
 python peopleCounter.py -c  # Attempts to detect people using webcam
-
-IMPORTANT: This example is given AS IT IS without any warranty
-
-Made by: Jose Garcia
-
 '''
 
-URL_EDUCATIONAL = "http://things.ubidots.com"
-URL_INDUSTRIAL = "http://industrial.api.ubidots.com"
-INDUSTRIAL_USER = False  # Set this to False if you are an educational user
-TOKEN = "A1E-VQSZw6exCjViKRfqHl7ISdrVEm3cG1"  # Put here your Ubidots TOKEN
-DEVICE = "detector"  # Device where will be stored the result
-VARIABLE = "people"  # Variable where will be stored the result
-
 HOGCV = cv2.HOGDescriptor()
 HOGCV.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
 
@@ -56,26 +44,6 @@ def buildPayload(variable, value, context):
     return {variable: {"value": value, "context": context}}
 
 
-def sendToUbidots(token, device, variable, value, context={}, industrial=True):
-    # Builds the endpoint
-    url = URL_INDUSTRIAL if industrial else URL_EDUCATIONAL
-    url = "{}/api/v1.6/devices/{}".format(url, device)
-
-    payload = buildPayload(variable, value, context)
-    headers = {"X-Auth-Token": token, "Content-Type": "application/json"}
-
-    attempts = 0
-    status = 400
-
-    while status >= 400 and attempts <= 5:
-        req = requests.post(url=url, headers=headers, json=payload)
-        status = req.status_code
-        attempts += 1
-        time.sleep(1)
-
-    return req
-
-
 def argsParser():
     ap = argparse.ArgumentParser()
     ap.add_argument("-i", "--image", default=None,
@@ -93,12 +61,12 @@ def localDetect(image_path):
     image = imutils.resize(image, width=min(400, image.shape[1]))
     clone = image.copy()
     if len(image) <= 0:
-        print("[ERROR] could not read your local image")
+        print("[ERROR] could not read local image")
         return result
     print("[INFO] Detecting people")
     result = detector(image)
 
-    # shows the result
+    """# shows the result
     for (xA, yA, xB, yB) in result:
         cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)
 
@@ -106,8 +74,8 @@ def localDetect(image_path):
     cv2.waitKey(0)
     cv2.destroyAllWindows()
 
-    cv2.imwrite("result.png", np.hstack((clone, image)))
+    cv2.imwrite("result.png", np.hstack((clone, image)))"""
-    return (result, image)
+    return result#(result, image)
 
 
 def cameraDetect(token, device, variable, sample_time=5):

camera/video_presence.py

@@ -20,6 +20,12 @@ args = vars(ap.parse_args())
 """ Determine opencv version and select tracker """
 # extract the OpenCV version info
 (major, minor) = cv2.__version__.split(".")[:2]
+# different methods of opencv require differing ways to unpack find countours
+if int(major) > 3:
+    OPENCV4=True
+else:
+    OPENCV4=False
+
 # if we are using OpenCV 3.2 or an earlier version, we can use a special factory
 # function to create the entity that tracks objects 
 if int(major) == 3 and int(minor) < 3:
@@ -62,8 +68,13 @@ now = ''
 framecounter = 0
 trackeron = 0
 people_count_total = 0
+frame_counter= 0
 
 while True:
+    """frame_counter+=1
+    if framecounter%5 != 0:
+        continue"""
+
     people_count_per_frame = 0
     frame = vs.read()
     frame = frame if args.get("video", None) is None else frame[1]
@@ -93,7 +104,10 @@ 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)
+        if OPENCV4:
+            cnts, im2  = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+        else:
+            _, 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: