use a regular subprocess for ffmpeg, refactor bounding box drawing

Dockerfile

@@ -1,5 +1,7 @@
 FROM ubuntu:18.04
 
+ARG DEVICE
+
 # Install packages for apt repo
 RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
     apt-transport-https \
@@ -8,11 +10,14 @@ RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
     wget \
     gnupg-agent \
     dirmngr \
-    software-properties-common
+    software-properties-common \
+    && rm -rf /var/lib/apt/lists/*
 
-RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys D986B59D
+COPY scripts/install_odroid_repo.sh .
 
-RUN echo "deb http://deb.odroid.in/5422-s bionic main" > /etc/apt/sources.list.d/odroid.list
+RUN if [ "$DEVICE" = "odroid" ]; then \
+      sh /install_odroid_repo.sh; \
+    fi
 
 RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
  python3 \ 
@@ -52,10 +57,12 @@ RUN  pip install -U pip \
  numpy \
  Flask \
  paho-mqtt \
- PyYAML \
- ffmpeg-python
+ PyYAML
 
 # Download & build OpenCV
+# TODO: use multistage build to reduce image size: 
+#   https://medium.com/@denismakogon/pain-and-gain-running-opencv-application-with-golang-and-docker-on-alpine-3-7-435aa11c7aec
+#   https://www.merixstudio.com/blog/docker-multi-stage-builds-python-development/
 RUN wget -q -P /usr/local/src/ --no-check-certificate https://github.com/opencv/opencv/archive/4.0.1.zip
 RUN cd /usr/local/src/ \
  && unzip 4.0.1.zip \
@@ -70,14 +77,15 @@ RUN cd /usr/local/src/ \
  && rm -rf /usr/local/src/opencv-4.0.1
 
 # Download and install EdgeTPU libraries for Coral
-RUN wget https://dl.google.com/coral/edgetpu_api/edgetpu_api_latest.tar.gz -O edgetpu_api.tar.gz --trust-server-names
+RUN wget https://dl.google.com/coral/edgetpu_api/edgetpu_api_latest.tar.gz -O edgetpu_api.tar.gz --trust-server-names \
+  && tar xzf edgetpu_api.tar.gz
+
+COPY scripts/install_edgetpu_api.sh edgetpu_api/install.sh
 
-RUN tar xzf edgetpu_api.tar.gz \
-  && cd edgetpu_api \
-  && cp -p libedgetpu/libedgetpu_arm32.so /usr/lib/arm-linux-gnueabihf/libedgetpu.so.1.0 \
-  && ldconfig \
-  && python3 -m pip install --no-deps "$(ls edgetpu-*-py3-none-any.whl 2>/dev/null)"
+RUN cd edgetpu_api \
+  && /bin/bash install.sh
 
+# Copy a python 3.6 version
 RUN cd /usr/local/lib/python3.6/dist-packages/edgetpu/swig/ \
   && ln -s _edgetpu_cpp_wrapper.cpython-35m-arm-linux-gnueabihf.so _edgetpu_cpp_wrapper.cpython-36m-arm-linux-gnueabihf.so
 

frigate/object_detection.py

@@ -89,8 +89,6 @@ class FramePrepper(threading.Thread):
                 cropped_frame = self.shared_frame[self.region_y_offset:self.region_y_offset+self.region_size, self.region_x_offset:self.region_x_offset+self.region_size].copy()
                 frame_time = self.frame_time.value
             
-            # convert to RGB
-            #cropped_frame_rgb = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2RGB)
             # Resize to 300x300 if needed
             if cropped_frame.shape != (300, 300, 3):
                 cropped_frame = cv2.resize(cropped_frame, dsize=(300, 300), interpolation=cv2.INTER_LINEAR)

frigate/objects.py

@@ -2,6 +2,7 @@ import time
 import datetime
 import threading
 import cv2
+from . util import draw_box_with_label
 
 class ObjectCleaner(threading.Thread):
     def __init__(self, objects_parsed, detected_objects):
@@ -79,12 +80,9 @@ class BestPersonFrame(threading.Thread):
             
             if not self.best_person is None and self.best_person['frame_time'] in recent_frames:
                 best_frame = recent_frames[self.best_person['frame_time']]
-                best_frame = cv2.cvtColor(best_frame, cv2.COLOR_BGR2RGB)
-                # draw the bounding box on the frame
-                color = (255,0,0)
-                cv2.rectangle(best_frame, (self.best_person['xmin'], self.best_person['ymin']), 
-                    (self.best_person['xmax'], self.best_person['ymax']), 
-                    color, 2)
 
-                # convert back to BGR
+                label = "{}: {}%".format(self.best_person['name'],int(self.best_person['score']*100))
+                draw_box_with_label(best_frame, self.best_person['xmin'], self.best_person['ymin'], 
+                    self.best_person['xmax'], self.best_person['ymax'], label)
+                
                 self.best_frame = cv2.cvtColor(best_frame, cv2.COLOR_RGB2BGR)

frigate/util.py

@@ -1,5 +1,26 @@
 import numpy as np
+import cv2
 
 # convert shared memory array into numpy array
 def tonumpyarray(mp_arr):
-    return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8)
+    return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8)
+
+def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label):
+    color = (255,0,0)
+    cv2.rectangle(frame, (x_min, y_min), 
+        (x_max, y_max), 
+        color, 2)
+    font_scale = 0.5
+    font = cv2.FONT_HERSHEY_SIMPLEX
+    # get the width and height of the text box
+    size = cv2.getTextSize(label, font, fontScale=font_scale, thickness=2)
+    text_width = size[0][0]
+    text_height = size[0][1]
+    line_height = text_height + size[1]
+    # set the text start position
+    text_offset_x = x_min
+    text_offset_y = 0 if y_min < line_height else y_min - line_height
+    # make the coords of the box with a small padding of two pixels
+    textbox_coords = ((text_offset_x, text_offset_y), (text_offset_x + text_width + 2, text_offset_y + line_height))
+    cv2.rectangle(frame, textbox_coords[0], textbox_coords[1], color, cv2.FILLED)
+    cv2.putText(frame, label, (text_offset_x, text_offset_y + line_height - 2), font, fontScale=font_scale, color=(0, 0, 0), thickness=2)

frigate/video.py

@@ -5,9 +5,10 @@ import cv2
 import threading
 import ctypes
 import multiprocessing as mp
+import subprocess as sp
 import numpy as np
 import ffmpeg
-from . util import tonumpyarray
+from . util import tonumpyarray, draw_box_with_label
 from . object_detection import FramePrepper
 from . objects import ObjectCleaner, BestPersonFrame
 from . mqtt import MqttObjectPublisher
@@ -16,34 +17,29 @@ from . mqtt import MqttObjectPublisher
 def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_shape, rtsp_url):
     # convert shared memory array into numpy and shape into image array
     arr = tonumpyarray(shared_arr).reshape(frame_shape)
-
-    ffmpeg_process = (
-        ffmpeg
-        .input(rtsp_url, 
-            rtsp_transport="tcp", 
-            stimeout=5000000, 
-            use_wallclock_as_timestamps=1,
-            fflags="+genpts",
-            avoid_negative_ts="make_zero")
-        .output('pipe:', format='rawvideo', pix_fmt='rgb24')
-    )
-
-    print(ffmpeg_process.compile())
-
-    ffmpeg_process = ffmpeg_process.run_async(pipe_stdout=True)
+    frame_size = frame_shape[0] * frame_shape[1] * frame_shape[2]
+
+    ffmpeg_cmd = ['ffmpeg', 
+        '-avoid_negative_ts', 'make_zero', 
+        '-fflags', '+genpts', 
+        '-rtsp_transport', 'tcp', 
+        '-stimeout', '5000000', 
+        '-use_wallclock_as_timestamps', '1', 
+        '-i', rtsp_url, 
+        '-f', 'rawvideo', 
+        '-pix_fmt', 'rgb24', 
+        'pipe:']
+    
+    pipe = sp.Popen(ffmpeg_cmd, stdout = sp.PIPE, bufsize=frame_size)
 
     while True:
-        in_bytes = ffmpeg_process.stdout.read(frame_shape[0] * frame_shape[1] * frame_shape[2])
-        if not in_bytes:
-            print("No bytes received. Waiting 1 second before trying again.")
-            time.sleep(1)
-            continue
+        raw_image = pipe.stdout.read(frame_size)
         frame = (
             np
-            .frombuffer(in_bytes, np.uint8)
+            .frombuffer(raw_image, np.uint8)
             .reshape(frame_shape)
         )
-        # Lock access and update frame
+
         with frame_lock:
             shared_frame_time.value = datetime.datetime.now().timestamp()
             arr[:] = frame
@@ -51,7 +47,7 @@ def fetch_frames(shared_arr, shared_frame_time, frame_lock, frame_ready, frame_s
         with frame_ready:
             frame_ready.notify_all()
 
-    ffmpeg_process.wait()
+    pipe.stdout.flush()
 
 # Stores 2 seconds worth of frames when motion is detected so they can be used for other threads
 class FrameTracker(threading.Thread):
@@ -272,14 +268,10 @@ class Camera:
         with self.frame_lock:
             frame = self.shared_frame_np.copy()
 
-        # convert to RGB for drawing
-        #frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
         # draw the bounding boxes on the screen
         for obj in detected_objects:
-            color = (255,0,0)
-            cv2.rectangle(frame, (obj['xmin'], obj['ymin']), 
-                (obj['xmax'], obj['ymax']), 
-                color, 2)
+            label = "{}: {}%".format(obj['name'],int(obj['score']*100))
+            draw_box_with_label(frame, obj['xmin'], obj['ymin'], obj['xmax'], obj['ymax'], label)
 
         for region in self.regions:
             color = (255,255,255)
@@ -287,7 +279,7 @@ class Camera:
                 (region['x_offset']+region['size'], region['y_offset']+region['size']), 
                 color, 2)
 
-        # convert back to BGR
+        # convert to BGR
         frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
 
         return frame