revamp dockerfile

Dockerfile

@@ -1,109 +1,49 @@
-FROM ubuntu:18.04
-
-ARG DEVICE
+FROM debian:buster-slim
+LABEL maintainer "blakeb@blakeshome.com"
 
+ENV DEBIAN_FRONTEND=noninteractive
 # Install packages for apt repo
-RUN apt-get -qq update && apt-get -qq install --no-install-recommends -y \
-    apt-transport-https \
-    ca-certificates \
-    curl \
-    wget \
-    gnupg-agent \
-    dirmngr \
-    software-properties-common \
-    && rm -rf /var/lib/apt/lists/*
-
-COPY scripts/install_odroid_repo.sh .
-
-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 \ 
- # OpenCV dependencies
- ffmpeg \
- build-essential \
- cmake \
- unzip \
- pkg-config \
- libjpeg-dev \
- libpng-dev \
- libtiff-dev \
- libavcodec-dev \
- libavformat-dev \
- libswscale-dev \
- libv4l-dev \
- libxvidcore-dev \
- libx264-dev \
- libgtk-3-dev \
- libatlas-base-dev \
- gfortran \
- python3-dev \
- # Coral USB Python API Dependencies
- libusb-1.0-0 \
- python3-pip \
- python3-pil \
- python3-numpy \
- python3-prctl \
- libc++1 \
- libc++abi1 \
- libunwind8 \
- libgcc1 \
- # VAAPI drivers for Intel hardware accel
- libva-drm2 libva2 i965-va-driver vainfo \
- && rm -rf /var/lib/apt/lists/* 
-
-# 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 \
- && rm 4.0.1.zip \
- && cd /usr/local/src/opencv-4.0.1/ \
- && mkdir build \
- && cd /usr/local/src/opencv-4.0.1/build \ 
- && cmake -D CMAKE_INSTALL_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local/ .. \
- && make -j4 \
- && make install \
- && ldconfig \
- && 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 \
-  && tar xzf edgetpu_api.tar.gz
-
-COPY scripts/install_edgetpu_api.sh edgetpu_api/install.sh
-
-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
+RUN apt -qq update && apt -qq install --no-install-recommends -y \
+    gnupg wget \
+    ffmpeg \
+    python3 \
+    python3-pip \
+    # python-prctl
+    build-essential libcap-dev \
+    # pillow-simd
+    zlib1g-dev libjpeg-dev python3-dev\
+    # VAAPI drivers for Intel hardware accel
+    libva-drm2 libva2 i965-va-driver vainfo \
+    && echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \
+    && wget -q -O - https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - \
+    && apt -qq update \
+    && echo "libedgetpu1-max libedgetpu/accepted-eula boolean true" | debconf-set-selections \
+    && apt -qq install --no-install-recommends -y \
+    libedgetpu1-max \
+    python3-edgetpu \
+    && rm -rf /var/lib/apt/lists/* \
+    && (apt-get autoremove -y; apt-get autoclean -y)
+
+# needs to be installed before others
+RUN pip3 install -U wheel setuptools
+
+RUN pip3 install -U \
+    opencv-python \
+    python-prctl \
+    numpy \
+    Flask \
+    paho-mqtt \
+    PyYAML \
+    matplotlib \
+    scipy \
+    pillow-simd
 
 # symlink the model and labels
-RUN wget https://dl.google.com/coral/canned_models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite -O mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite --trust-server-names
-RUN wget https://dl.google.com/coral/canned_models/coco_labels.txt -O coco_labels.txt --trust-server-names
+RUN wget -q https://github.com/google-coral/edgetpu/raw/master/test_data/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite -O mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite --trust-server-names
+RUN wget -q https://dl.google.com/coral/canned_models/coco_labels.txt -O coco_labels.txt --trust-server-names
 RUN ln -s mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite /frozen_inference_graph.pb
 RUN ln -s /coco_labels.txt /label_map.pbtext
 
-# Minimize image size 
-RUN (apt-get autoremove -y; \
-     apt-get autoclean -y)
-
-# Install core packages 
-RUN wget -q -O /tmp/get-pip.py --no-check-certificate https://bootstrap.pypa.io/get-pip.py && python3 /tmp/get-pip.py
-RUN  pip install -U pip \
- numpy \
- Flask \
- paho-mqtt \
- PyYAML \
- matplotlib \
- scipy
-
 WORKDIR /opt/frigate/
 ADD frigate frigate/
 COPY detect_objects.py .

benchmark.py

@@ -14,7 +14,7 @@ flattened_frame = np.expand_dims(frame, axis=0).flatten()
 detection_times = []
 
 for x in range(0, 1000):
-    objects = engine.DetectWithInputTensor(flattened_frame, threshold=0.1, top_k=3)
+    objects = engine.detect_with_input_tensor(flattened_frame, threshold=0.1, top_k=3)
     detection_times.append(engine.get_inference_time())
 
 print("Average inference time: " + str(statistics.mean(detection_times)))

frigate/object_detection.py

@@ -32,7 +32,7 @@ class PreppedQueueProcessor(threading.Thread):
             frame = self.prepped_frame_queue.get()
 
             # Actual detection.
-            frame['detected_objects'] = self.engine.DetectWithInputTensor(frame['frame'], threshold=0.2, top_k=5)
+            frame['detected_objects'] = self.engine.detect_with_input_tensor(frame['frame'], threshold=0.2, top_k=5)
             self.fps.update()
             self.avg_inference_speed = (self.avg_inference_speed*9 + self.engine.get_inference_time())/10
 

frigate/objects.py

@@ -152,8 +152,6 @@ class RegionRefiner(threading.Thread):
                     })
                     self.camera.dynamic_region_fps.update()
                     look_again = True
-                # TODO: zoom in on unclipped low confidence objects
-                # else: ...
 
             # if we are looking again, then this frame is not ready for processing
             if look_again: