.gitignore

@@ -7,4 +7,3 @@ camera/videos
 *.jpg
 *.h264
 *.mp4
-*.png

camera/counter_people.py

@@ -1,160 +0,0 @@
-from imutils.object_detection import non_max_suppression
-import numpy as np
-import imutils
-import cv2
-import requests
-import time
-import argparse
-import time
-import base64
-
-'''
-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
-'''
-
-HOGCV = cv2.HOGDescriptor()
-HOGCV.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
-
-def detector(image):
-    '''
-    @image is a numpy array
-    '''
-
-    clone = image.copy()
-
-    (rects, weights) = HOGCV.detectMultiScale(image, winStride=(4, 4),
-                                              padding=(8, 8), scale=1.05)
-
-    # draw the original bounding boxes
-    for (x, y, w, h) in rects:
-        cv2.rectangle(clone, (x, y), (x + w, y + h), (0, 0, 255), 2)
-
-    # Applies non-max supression from imutils package to kick-off overlapped
-    # boxes
-    rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])
-    result = non_max_suppression(rects, probs=None, overlapThresh=0.65)
-
-    return result
-
-
-def buildPayload(variable, value, context):
-    return {variable: {"value": value, "context": context}}
-
-
-def argsParser():
-    ap = argparse.ArgumentParser()
-    ap.add_argument("-i", "--image", default=None,
-                    help="path to image test file directory")
-    ap.add_argument("-c", "--camera", default=False,
-                    help="Set as true if you wish to use the camera")
-    args = vars(ap.parse_args())
-
-    return args
-
-
-def localDetect(image_path):
-    result = []
-    image = cv2.imread(image_path)
-    image = imutils.resize(image, width=min(400, image.shape[1]))
-    clone = image.copy()
-    if len(image) <= 0:
-        print("[ERROR] could not read local image")
-        return result
-    print("[INFO] Detecting people")
-    result = detector(image)
-
-    """# shows the result
-    for (xA, yA, xB, yB) in result:
-        cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)
-
-    cv2.imshow("result", image)
-    cv2.waitKey(0)
-    cv2.destroyAllWindows()
-
-    cv2.imwrite("result.png", np.hstack((clone, image)))"""
-    return result#(result, image)
-
-
-def cameraDetect(token, device, variable, sample_time=5):
-
-    cap = cv2.VideoCapture(0)
-    init = time.time()
-
-    # Allowed sample time for Ubidots is 1 dot/second
-    if sample_time < 1:
-        sample_time = 1
-
-    while(True):
-        # Capture frame-by-frame
-        ret, frame = cap.read()
-        frame = imutils.resize(frame, width=min(400, frame.shape[1]))
-        result = detector(frame.copy())
-
-        # shows the result
-        #for (xA, yA, xB, yB) in result:
-        #    cv2.rectangle(frame, (xA, yA), (xB, yB), (0, 255, 0), 2)
-        #cv2.imshow('frame', frame)
-
-        # Sends results
-        if time.time() - init >= sample_time:
-            #print("[INFO] Sending actual frame results")
-            # Converts the image to base 64 and adds it to the context
-            #b64 = convert_to_base64(frame)
-            #context = {"image": b64}
-            if len(result):
-                print("{} people detected.".format(len(result)))
-            init = time.time()
-        
-
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            break
-
-    # When everything done, release the capture
-    cap.release()
-    cv2.destroyAllWindows()
-
-
-def convert_to_base64(image):
-    image = imutils.resize(image, width=400)
-    img_str = cv2.imencode('.png', image)[1].tostring()
-    b64 = base64.b64encode(img_str)
-
-    return b64.decode('utf-8')
-
-
-def detectPeople(args):
-    image_path = args["image"]
-    camera = True if str(args["camera"]) == 'true' else False
-
-    # Routine to read local image
-    if image_path != None and not camera:
-        print("[INFO] Image path provided, attempting to read image")
-        (result, image) = localDetect(image_path)
-        print("[INFO] sending results")
-        # Converts the image to base 64 and adds it to the context
-        b64 = convert_to_base64(image)
-        context = {"image": b64}
-        print(len(result))
-        # Sends the result
-        """req = sendToUbidots(TOKEN, DEVICE, VARIABLE,
-                            len(result), context=context)
-        if req.status_code >= 400:
-            print("[ERROR] Could not send data to Ubidots")
-            return req"""
-
-    # Routine to read images from webcam
-    if camera:
-        print("[INFO] reading camera images")
-        cameraDetect(TOKEN, DEVICE, VARIABLE)
-
-
-def main():
-    args = argsParser()
-    detectPeople(args)
-
-
-if __name__ == '__main__':
-    main()

camera/video_presence.py

@@ -20,12 +20,6 @@ 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:
@@ -68,13 +62,8 @@ 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]
@@ -104,9 +93,6 @@ 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)
-        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))