Commit 30e34b87 authored by Juan Diego Gonzales Zuniga's avatar Juan Diego Gonzales Zuniga
Browse files

Update for benchmark

parent 4240cd68
FROM local/dockervino:phase1 as build
FROM ubuntu18_data_dev:2021.3 as build
USER root
ENV downloader=${INTEL_OPENVINO_DIR}/deployment_tools/tools/model_downloader/downloader.py
ENV converter=${INTEL_OPENVINO_DIR}/deployment_tools/tools/model_downloader/converter.py
ENV optimizer=${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py
ARG models=/root/openvino_models
WORKDIR $models
RUN apt update && \
apt install sudo && \
${INTEL_OPENVINO_DIR}/deployment_tools/demo/demo_benchmark_app.sh
RUN python3 $downloader --name googlenet-v3 --output_dir $models
RUN python3 $converter --name googlenet-v3 --output_dir $models --precisions FP32,FP16
......@@ -20,5 +26,17 @@ RUN python3 $converter --name vgg19 --output_dir $models --precisions FP32,FP16
RUN python3 $downloader --name resnet-50-tf --output_dir $models
RUN python3 $converter --name resnet-50-tf --output_dir $models --precisions FP32,FP16
RUN python3 $downloader --name efficientnet-b0-pytorch --output_dir $models
RUN python3 $converter --name efficientnet-b0-pytorch --output_dir $models --precisions FP32,FP16
RUN python3 $downloader --name efficientnet-b5-pytorch --output_dir $models
RUN python3 $converter --name efficientnet-b5-pytorch --output_dir $models --precisions FP32,FP16
RUN python3 $downloader --name efficientnet-b7-pytorch --output_dir $models
RUN python3 $converter --name efficientnet-b7-pytorch --output_dir $models --precisions FP32,FP16
RUN python3 $downloader --name i3d-rgb-tf --output_dir $models
RUN python3 $converter --name i3d-rgb-tf --output_dir $models --precisions FP32,FP16
COPY ./entrypoint.sh /
CMD ["/bin/bash"]
......@@ -4,25 +4,36 @@ source $setupvars
# app, device, model and input are defined in the runcmd file
benchmark=/root/inference_engine_samples_build/intel64/Release/benchmark_app
input=/opt/intel/openvino/deployment_tools/demo/car.png
models=/root/openvino_models
echo "Benchmarking starts now!"
lscpu
echo "Inception V3"
$benchmark -d $device -i $input -api $api -pc -m $models/public/googlenet-v3/$datatype/googlenet-v3.xml
$benchmark -d $device -api $api -pc -m $models/public/googlenet-v3/$datatype/googlenet-v3.xml
echo "Inception V4"
$benchmark -d $device -i $input -api $api -pc -m $models/public/googlenet-v4-tf/$datatype/googlenet-v4-tf.xml
$benchmark -d $device -api $api -pc -m $models/public/googlenet-v4-tf/$datatype/googlenet-v4-tf.xml
echo "VGG16"
$benchmark -d $device -i $input -api $api -pc -m $models/public/vgg16/$datatype/vgg16.xml
$benchmark -d $device -api $api -pc -m $models/public/vgg16/$datatype/vgg16.xml
echo "VGG19"
$benchmark -d $device -i $input -api $api -pc -m $models/public/vgg19/$datatype/vgg19.xml
$benchmark -d $device -api $api -pc -m $models/public/vgg19/$datatype/vgg19.xml
echo "Resnet 50"
$benchmark -d $device -i $input -api $api -pc -m $models/public/resnet-50-tf/$datatype/resnet-50-tf.xml
$benchmark -d $device -api $api -pc -m $models/public/resnet-50-tf/$datatype/resnet-50-tf.xml
echo "Efficientnet B0"
$benchmark -d $device -api $api -pc -m $models/public/efficientnet-b0-pytorch/$datatype/efficientnet-b0-pytorch.xml
echo "Efficientnet B5"
$benchmark -d $device -api $api -pc -m $models/public/efficientnet-b5-pytorch/$datatype/efficientnet-b5-pytorch.xml
echo "Efficientnet B7"
$benchmark -d $device -api $api -pc -m $models/public/efficientnet-b7-pytorch/$datatype/efficientnet-b7-pytorch.xml
echo "I3D"
$benchmark -d $device -api $api -pc -m $models/public/i3d-rgb-tf/$datatype/i3d-rgb-tf.xml
echo "Benchmarking done!"
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