diff --git a/README.md b/README.md
index 5bb476e..e799671 100644
--- a/README.md
+++ b/README.md
@@ -11,17 +11,23 @@
 
 ## Build person-detection
 ```
-make build
+make docker-build
 ```
 
 ## Start RPi camera
+### M-JPEG
 ```
 gst-launch-1.0 rpicamsrc bitrate=1000000 ! video/x-raw,width=640,height=480,framerate=25/1,profile=baseline ! jpegenc ! rtpjpegpay ! udpsink host=10.128.99.49 port=5000
 ```
 
-## Start persion-detection
+### H.264
 ```
-make run
+gst-launch-1.0 rpicamsrc bitrate=1000000 ! video/x-h264,width=640,height=480,framerate=15/1 ! h264parse ! rtph264pay config-interval=10 pt=96 ! udpsink host=10.128.99.49 port=5000
+```
+
+## Start person-detection-app
+```
+make docker-run
 ```
 
 ## Quick test
diff --git a/docker/Dockerfile b/docker/Dockerfile
index 882c5d0..7cfcbfa 100644
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -25,4 +25,4 @@
      pip3 install -r requirements.txt
 
 ENTRYPOINT ["./bin/person_detection.sh"]
-CMD ["-i gstreamer"]
+CMD ["-i gstreamer -pt 0.75"]
diff --git a/person_detection/person_detection.py b/person_detection/person_detection.py
index e321be8..3d1fe80 100644
--- a/person_detection/person_detection.py
+++ b/person_detection/person_detection.py
@@ -104,8 +104,8 @@
 
         # Async doesn't work if True
         # Request issues = Runtime Error: [REQUEST BUSY]
-        self.is_async_mode = False
-        #is_async_mode = True
+        # self.is_async_mode = False
+        self.is_async_mode = True
         render_time = 0
         ret, frame = self.cap.read()
 
@@ -118,8 +118,8 @@
                 ret, frame = self.cap.read()
             if not ret:
                 break
-            initial_w = self.cap.get(3)
-            initial_h = self.cap.get(4)
+            initial_w = self.cap.get(cv2.CAP_PROP_FRAME_WIDTH)
+            initial_h = self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
 
             # Main sync point:
             # in the truly Async mode we start the NEXT infer request, while waiting for the CURRENT to complete
@@ -152,7 +152,7 @@
                         ymax = int(obj[6] * initial_h)
                         class_id = int(obj[1])
                         # Draw box and label\class_id
-                        color = (min(class_id * 12.5, 255),min(class_id * 7, 255), min(class_id * 5, 255))
+                        color = (0, 0, 255)
                         cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), color, 2)
                         det_label = self.labels_map[class_id] if self.labels_map else str(class_id)
                         cv2.putText(frame, det_label + ' ' + str(round(obj[2] * 100, 1)) + ' %', (xmin, ymin - 7),