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pi_for_openvino.dockerfile
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pi_for_openvino.dockerfile
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FROM balenalib/rpi-raspbian:latest
ARG DOWNLOAD_LINK=https://download.01.org/opencv/2020/openvinotoolkit/2020.3/l_openvino_toolkit_runtime_raspbian_p_2020.3.220.tgz
ARG INSTALL_DIR=/opt/intel/openvino
ARG BIN_FILE=https://download.01.org/opencv/2019/open_model_zoo/R3/20190905_163000_models_bin/person-vehicle-bike-detection-crossroad-0078/FP16/person-vehicle-bike-detection-crossroad-0078.bin
ARG WEIGHTS_FILE=https://download.01.org/opencv/2019/open_model_zoo/R3/20190905_163000_models_bin/person-vehicle-bike-detection-crossroad-0078/FP16/person-vehicle-bike-detection-crossroad-0078.xml
ARG IMAGE_FILE=https://cdn.pixabay.com/photo/2018/07/06/00/33/person-3519503_960_720.jpg
RUN apt-get update && apt-get install -y --no-install-recommends \
apt-utils \
automake \
cmake \
cpio \
gcc \
g++ \
libatlas-base-dev \
libstdc++6 \
libtool \
libusb-1.0.0-dev \
lsb-release \
make \
python3-pip \
python3-numpy \
python3-scipy \
libgtk-3-0 \
pkg-config \
libavcodec-dev \
libavformat-dev \
libswscale-dev \
sudo \
udev \
unzip \
vim \
libpython3.7 \
usbutils \
wget && \
rm -rf /var/lib/apt/lists/*
RUN mkdir -p $INSTALL_DIR && cd $INSTALL_DIR && \
wget -c $DOWNLOAD_LINK && \
tar xf l_openvino_toolkit_runtime_raspbian_p*.tgz --strip 1 -C $INSTALL_DIR
# add USB rules
RUN sudo usermod -a -G users "$(whoami)" && \
/bin/bash -c "source $INSTALL_DIR/bin/setupvars.sh && \
sh $INSTALL_DIR/install_dependencies/install_NCS_udev_rules.sh"
# build Object Detection sample
RUN echo "source /opt/intel/openvino/bin/setupvars.sh" >> ~/.bashrc && \
mkdir /root/Downloads && \
cd $INSTALL_DIR/deployment_tools/inference_engine/samples/c/ && \
/bin/bash -c "source $INSTALL_DIR/bin/setupvars.sh && \
./build_samples.sh && \
wget --no-check-certificate $BIN_FILE -O /root/Downloads/person-vehicle-bike-detection-crossroad-0078.bin && \
wget --no-check-certificate $WEIGHTS_FILE -O /root/Downloads/person-vehicle-bike-detection-crossroad-0078.xml && \
wget --no-check-certificate $IMAGE_FILE -O /root/Downloads/walk.jpg "
RUN echo "import cv2 as cv\n\
# Load the model.\n\
net = cv.dnn.readNet('person-vehicle-bike-detection-crossroad-0078.xml',\
'person-vehicle-bike-detection-crossroad-0078.bin')\n\
# Specify target device.\n\
net.setPreferableTarget(cv.dnn.DNN_TARGET_MYRIAD)\n\
# Read an image.\n\
frame = cv.imread('walk.jpg')\n\
if frame is None:\n\
raise Exception('Image not found!')\n\
# Prepare input blob and perform an inference.\n\
blob = cv.dnn.blobFromImage(frame, size=(1024, 1024), ddepth=cv.CV_8U)\n\
net.setInput(blob)\n\
out = net.forward()\n\
# Draw detected faces on the frame.\n\
for detection in out.reshape(-1, 7):\n\
confidence = float(detection[2])\n\
xmin = int(detection[3] * frame.shape[1])\n\
ymin = int(detection[4] * frame.shape[0])\n\
xmax = int(detection[5] * frame.shape[1])\n\
ymax = int(detection[6] * frame.shape[0])\n\
if confidence > 0.5:\n\
cv.rectangle(frame, (xmin, ymin), (xmax, ymax), color=(0, 255, 0))\n\
# Save the frame to an image file.\n\
cv.imwrite('out.png', frame)\n\
print('Detection results in out.png')" >> /root/Downloads/openvino_fd_myriad.py
RUN echo "import cv2 as cv\n\
from openvino.inference_engine import IECore\n\
ie = IECore()\n\
# Load the model.\n\
net = ie.read_network('person-vehicle-bike-detection-crossroad-0078.xml',\
'person-vehicle-bike-detection-crossroad-0078.bin')\n\
input_blob = next(iter(net.inputs))\n\
output_blob = next(iter(net.outputs))\n\
net.batch_size = 1\n\
_, _, height, width = net.inputs[input_blob].shape\n\
# Read an image.\n\
frame = cv.imread('walk.jpg')\n\
if frame is None:\n\
raise Exception('Image not found!')\n\
# Prepare input blob and perform an inference.\n\
blob = cv.dnn.blobFromImage(frame, size=(1024, 1024), ddepth=cv.CV_8U)\n\
exec_net = ie.load_network(network=net, device_name=ie.available_devices[0])\n\
res = exec_net.infer(inputs={input_blob: blob})\n\
out = res[output_blob][0]\n\
# Draw detected faces on the frame.\n\
for detection in out.reshape(-1, 7):\n\
confidence = float(detection[2])\n\
xmin = int(detection[3] * frame.shape[1])\n\
ymin = int(detection[4] * frame.shape[0])\n\
xmax = int(detection[5] * frame.shape[1])\n\
ymax = int(detection[6] * frame.shape[0])\n\
if confidence > 0.5:\n\
cv.rectangle(frame, (xmin, ymin), (xmax, ymax), color=(0, 255, 0))\n\
# Save the frame to an image file.\n\
cv.imwrite('out.png', frame)\n\
print('Detection results in out.png')" >> /root/Downloads/openvino_myriad.py
WORKDIR /root/Downloads
ENTRYPOINT "source /opt/intel/openvino/bin/setupvars.sh" ; "/bin/bash"