fixed multiple box bug

server/app.py

@@ -16,10 +16,10 @@ application = Flask(__name__)
 clients = []
 cams = []
 lastImages = list(range(0,4))
-with open("./server/clients.json", 'r', encoding='utf-8') as f:
+with open("./clients.json", 'r', encoding='utf-8') as f:
     clients = json.loads(f.read())
 
-with open("./server/cams.json", 'r', encoding='utf-8') as f:
+with open("./cams.json", 'r', encoding='utf-8') as f:
     cams = json.loads(f.read())
 
 class VideoCamera(object):
@@ -78,7 +78,10 @@ def main():
                     print("request error")
 
             tmp = time.time()
-            img, result = detector.detect(stream) 
+            try:
+                img, result = detector.detect(stream) 
+            except:
+                continue
             print(cam["client_id"], result, time.time()-tmp)
             lastImages[cam["id"]] = img
 

server/cams.json

@@ -2,7 +2,7 @@
   {
     "id": 0,
     "label": "cam1",
-    "ip": "http://89.29.108.38:80/mjpg/video.mjpg",
+    "ip": "http://77.22.202.109/mjpg/video.mjpg",
     "client_id": 0,
     "status": false,
     "x":0.2,
@@ -22,7 +22,7 @@
   {
     "id": 2,
     "label": "cam3",
-    "ip": "http://62.99.80.154:81/mjpg/video.mjpg",
+    "ip": "http://89.29.108.38:80/mjpg/video.mjpg",
     "client_id": 2,
     "status": false,
     "x":0.9,

server/detector.py

@@ -60,9 +60,9 @@ class DetectorAPI:
 
 class Detector:
     def __init__(self):
-        self.model_path = "./server/model.pb"
+        self.model_path = "./model.pb"
         self.odapi = DetectorAPI(path_to_ckpt=self.model_path)
-        self.threshold = 0.3       
+        self.threshold = 0.7       
 
     def detect(self, stream):
         cap = cv2.VideoCapture(stream)
@@ -70,20 +70,20 @@ class Detector:
         r, img = cap.read()
         if img is None:
             return img
-        img = cv2.resize(img, (720, 480))
+        img = cv2.resize(img, (1000, 543))
 
         boxes, scores, classes, num = self.odapi.process_frame(img)
-
+        res = False
         for i in range(len(boxes)):
             # Class 1 represents human
             if classes[i] == 1:
                 if scores[i] > self.threshold:
                     box = boxes[i]
                     cv2.rectangle(img, (box[1], box[0]), (box[3], box[2]), (255, 0, 0), 2)
-                    return img, True
+                    res = True
                 else:
-                    return img, False
+                    res = False
-
+        return img, res
             
     #def __del__(self):
 

server/main.py

@@ -1,37 +0,0 @@
-import time
-import requests
-import detector as dt
-import cv2
-
-if __name__ == "__main__":
-    t = 1  # seconds a person can leave the room for
-    t0 = time.time()
-    time.clock()    
-    elapsed = 0
-    #stream = "https://192.168.178.56:8080/video"
-    stream = "http://217.128.254.187:8083/mjpg/video.mjpg"
-    detector = dt.Detector(stream)
-    music_playing = False
-
-    #cv2.startWindowThread()
-    #cv2.namedWindow("preview")
-
-    while True:
-        elapsed = time.time() - t0
-        if elapsed > t and music_playing:
-            r = requests.get("http://192.168.178.53/stop")
-            if r.status_code == 200:
-                music_playing = False
-        tmp = time.time()
-        img = detector.detect()
-        print(time.time()-tmp)
-        if img is not None and not music_playing:
-            r = requests.get("http://192.168.178.53/play")
-            if r.status_code == 200:
-                music_playing = True
-                t0 = time.time()
-        
-
-        cv2.imshow("preview", img)
-        cv2.waitKey(1)
-        

server/requirements.txt

@@ -1,4 +1,6 @@
 requests
 flask
 gunicorn
-opencv-python
+opencv-python
+tensorflow
+numpy