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Commit 715b8c61 authored by GONZALES ZUNIGA Juan Diego's avatar GONZALES ZUNIGA Juan Diego
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Build reworked 

-Now the demos are built with the openvino_model_zoo repo fork
-Phase2 is within phase1
-phase3 is moved to phase2
-phase3 is the bulidng repo block
-execute mode for scripts is changed
parent d875b095
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benchmark/buildcmd 100644 → 100755
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benchmark/runcmd 100644 → 100755
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debug/buildcmd 100644 → 100755
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debug/runcmd 100644 → 100755
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demo/buildcmd 100644 → 100755
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demo/runcmd 100644 → 100755
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......@@ -24,7 +24,7 @@ setupvars=/opt/intel/openvino/bin/setupvars.sh
examples_dir=/root/omz_demos_build/intel64/Release
models_dir=/root/openvino_models/ir
# Input: IPCam or USBCam
input=cam #input=http://94.214.173.241:8001/mjpg/video.mjpg
input=http://71.73.8.17:8080/cam_1.cgi #input=http://94.214.173.241:8001/mjpg/video.mjpg
#################################
######## Examples ###########
......
phase1/Dockerfile
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......@@ -40,15 +40,16 @@ RUN tar xf $openvinoTar.tgz && cd $openvinoTar && \
RUN bash $INSTALL_DIR/install_dependencies/install_openvino_dependencies.sh
# build Inference Engine Samples
RUN $INSTALL_DIR/deployment_tools/inference_engine/samples/build_samples.sh
RUN $INSTALL_DIR/deployment_tools/inference_engine/demos/build_demos.sh
# RUN $INSTALL_DIR/deployment_tools/inference_engine/samples/build_samples.sh
# RUN $INSTALL_DIR/deployment_tools/inference_engine/demos/build_demos.sh
# install model_optimizer requisites needs tf 1.15 for kontron
RUN sed -i 's/>=1.2.0/==1.5.0/g' $INSTALL_DIR/deployment_tools/model_optimizer/requirements.txt
#RUN sed -i 's/>=1.2.0/==1.5.0/g' $INSTALL_DIR/deployment_tools/model_optimizer/requirements_tf.txt
RUN $INSTALL_DIR/deployment_tools/model_optimizer/install_prerequisites/install_prerequisites.sh
# inti openvino env
# init openvino env
RUN echo "source $INSTALL_DIR/bin/setupvars.sh" >> /root/.bashrc
# check installation with example
RUN $INSTALL_DIR/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
CMD ["/bin/bash"]
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phase2/Dockerfile
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# Compilation of examples for openVino
# Compilation demo_squeezenet_download_conver_run and security_barrier_camera
# Docker image after installation
# Downloads model ssd300 and creates yolov3
FROM local/dockervino:phase1_R3 as build
FROM local/dockervino:phase1_R3
MAINTAINER jdg:juan-diego.gonzales-zuniga@kontron.com
ARG INSTALL_DIR=/opt/intel/openvino
WORKDIR $INSTALL_DIR/deployment_tools/demo
#RUN sed -i 's/source "/"/g' $INSTALL_DIR/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
#RUN sed -i 's:"install_prerequisites.sh":"./install_prerequisites.sh":g' /opt/intel/openvino/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
#RUN sed -i 's:make -j8 classification_sample:make -j8:g' /opt/intel/openvino/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
RUN $INSTALL_DIR/deployment_tools/demo/demo_squeezenet_download_convert_run.sh
ARG downloader=$INSTALL_DIR/deployment_tools/tools/model_downloader/downloader.py
ARG optimizer=$INSTALL_DIR/deployment_tools/model_optimizer
ARG models=/root/openvino_models
# Downloading SSD Detection
RUN python3 $downloader --name ssd300 --output_dir $models
RUN python3 $optimizer/mo.py \
--input_model $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel \
--input_proto $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/deploy.prototxt \
--output_dir $models/ir/ssd300/FP32 --model_name ssd300 --data_type FP32
RUN python3 $optimizer/mo.py \
--input_model $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel \
--input_proto $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/deploy.prototxt \
--output_dir $models/ir/ssd300/FP16 --model_name ssd300 --data_type FP16
# Downloading Human Pose Detection
RUN python3 $downloader --name human-pose-estimation-0001 --output_dir $models/ir
# Downloading Face Detection
RUN python3 $downloader --name face-detection-retail-0004 --output_dir $models/ir
# Downloading Age gender Recognition
RUN python3 $downloader --name age-gender-recognition-retail-0013 --output_dir $models/ir
# Downloaing Emotion Recognition
RUN python3 $downloader --name emotions-recognition-retail-0003 --output_dir $models/ir
# Downloading Head Pose Estimation
RUN python3 $downloader --name head-pose-estimation-adas-0001 --output_dir $models/ir
WORKDIR $models
# Clone Yolo V3 tensorflow
RUN git clone https://github.com/mystic123/tensorflow-yolo-v3
WORKDIR $models/tensorflow-yolo-v3
# Download weights of Yolov3 and Yolov3Tiny
RUN wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names && \
wget https://pjreddie.com/media/files/yolov3.weights && \
wget https://pjreddie.com/media/files/yolov3-tiny.weights
RUN python3 convert_weights_pb.py --class_names coco.names \
--data_format NHWC --weights_file yolov3.weights --output_graph yolo_v3.pb
RUN python3 convert_weights_pb.py --class_names coco.names \
--data_format NHWC --weights_file yolov3-tiny.weights \
--output_graph yolo_v3_tiny.pb --tiny
# Optimizer on Yolov3
COPY ./yolo_v3.json $models/tensorflow-yolo-v3
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP32 \
--model_name yolo_v3 \
--data_type FP32
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP16 \
--model_name yolo_v3 \
--data_type FP16
# Optimizer on Yolov3Tiny
COPY ./yolo_v3_tiny.json $models/tensorflow-yolo-v3
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3_tiny.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3_tiny.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP32 \
--model_name yolo_v3_tiny \
--data_type FP32
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3_tiny.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3_tiny.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP16 \
--model_name yolo_v3_tiny \
--data_type FP16
WORKDIR $models
# Download smallest maskrcnn
RUN wget http://download.tensorflow.org/models/object_detection/mask_rcnn_inception_v2_coco_2018_01_28.tar.gz
RUN tar -xzf mask_rcnn_inception_v2_coco_2018_01_28.tar.gz
# Optimizer on maskrcnn
RUN python3 $optimizer/mo_tf.py \
--input_model $models/mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb \
--tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json \
--tensorflow_object_detection_api_pipeline $models/mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config \
--output_dir $models/ir/mask_rcnn/FP32 \
--model_name mask_rcnn_inception_v2 \
--data_type FP32 --reverse_input_channels
RUN python3 $optimizer/mo_tf.py \
--input_model $models/mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb \
--tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json \
--tensorflow_object_detection_api_pipeline $models/mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config \
--output_dir $models/ir/mask_rcnn/FP16 \
--model_name mask_rcnn_inception_v2 \
--data_type FP16 --reverse_input_channels
# Download tracker networks
RUN $downloader --name person-detection-retail-0013 --output_dir $models/ir
RUN $downloader --name person-reidentification-retail-0031 --output_dir $models/ir
CMD ["/bin/bash"]
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phase3/Dockerfile
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# Docker image after installation
# Downloads model ssd300 and creates yolov3
# Compilation of examples for openVino
# Compilation demo_squeezenet_download_conver_run and security_barrier_camera
FROM local/dockervino:phase2_R3
FROM local/dockervino:phase2_R3 as build
MAINTAINER jdg:juan-diego.gonzales-zuniga@kontron.com
ARG INSTALL_DIR=/opt/intel/openvino
ARG downloader=$INSTALL_DIR/deployment_tools/tools/model_downloader/downloader.py
ARG optimizer=$INSTALL_DIR/deployment_tools/model_optimizer
ARG models=/root/openvino_models
# Downloading SSD Detection
RUN python3 $downloader --name ssd300 --output_dir $models
RUN python3 $optimizer/mo.py \
--input_model $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel \
--input_proto $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/deploy.prototxt \
--output_dir $models/ir/ssd300/FP32 --model_name ssd300 --data_type FP32
RUN python3 $optimizer/mo.py \
--input_model $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel \
--input_proto $models/public/ssd300/models/VGGNet/VOC0712Plus/SSD_300x300_ft/deploy.prototxt \
--output_dir $models/ir/ssd300/FP16 --model_name ssd300 --data_type FP16
# Downloading Human Pose Detection
RUN python3 $downloader --name human-pose-estimation-0001 --output_dir $models/ir
# Downloading Face Detection
RUN python3 $downloader --name face-detection-retail-0004 --output_dir $models/ir
# Downloading Age gender Recognition
RUN python3 $downloader --name age-gender-recognition-retail-0013 --output_dir $models/ir
# Downloaing Emotion Recognition
RUN python3 $downloader --name emotions-recognition-retail-0003 --output_dir $models/ir
# Downloading Head Pose Estimation
RUN python3 $downloader --name head-pose-estimation-adas-0001 --output_dir $models/ir
WORKDIR $models
# Clone Yolo V3 tensorflow
RUN git clone https://github.com/mystic123/tensorflow-yolo-v3
WORKDIR $models/tensorflow-yolo-v3
# Download weights of Yolov3 and Yolov3Tiny
RUN wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names && \
wget https://pjreddie.com/media/files/yolov3.weights && \
wget https://pjreddie.com/media/files/yolov3-tiny.weights
RUN python3 convert_weights_pb.py --class_names coco.names \
--data_format NHWC --weights_file yolov3.weights --output_graph yolo_v3.pb
RUN python3 convert_weights_pb.py --class_names coco.names \
--data_format NHWC --weights_file yolov3-tiny.weights \
--output_graph yolo_v3_tiny.pb --tiny
# Optimizer on Yolov3
COPY ./yolo_v3.json $models/tensorflow-yolo-v3
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP32 \
--model_name yolo_v3 \
--data_type FP32
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP16 \
--model_name yolo_v3 \
--data_type FP16
# Optimizer on Yolov3Tiny
COPY ./yolo_v3_tiny.json $models/tensorflow-yolo-v3
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3_tiny.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3_tiny.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP32 \
--model_name yolo_v3_tiny \
--data_type FP32
RUN python3 $optimizer/mo_tf.py \
--input_model $models/tensorflow-yolo-v3/yolo_v3_tiny.pb \
--tensorflow_use_custom_operations_config $models/tensorflow-yolo-v3/yolo_v3_tiny.json \
--input_shape [1,416,416,3] \
--output_dir $models/ir/yolo/FP16 \
--model_name yolo_v3_tiny \
--data_type FP16
WORKDIR $models
# Download smallest maskrcnn
RUN wget http://download.tensorflow.org/models/object_detection/mask_rcnn_inception_v2_coco_2018_01_28.tar.gz
RUN tar -xzf mask_rcnn_inception_v2_coco_2018_01_28.tar.gz
# Optimizer on maskrcnn
RUN python3 $optimizer/mo_tf.py \
--input_model $models/mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb \
--tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json \
--tensorflow_object_detection_api_pipeline $models/mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config \
--output_dir $models/ir/mask_rcnn/FP32 \
--model_name mask_rcnn_inception_v2 \
--data_type FP32 --reverse_input_channels
RUN python3 $optimizer/mo_tf.py \
--input_model $models/mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb \
--tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json \
--tensorflow_object_detection_api_pipeline $models/mask_rcnn_inception_v2_coco_2018_01_28/pipeline.config \
--output_dir $models/ir/mask_rcnn/FP16 \
--model_name mask_rcnn_inception_v2 \
--data_type FP16 --reverse_input_channels
# Download tracker networks
RUN $downloader --name person-detection-retail-0013 --output_dir $models/ir
RUN $downloader --name person-reidentification-retail-0031 --output_dir $models/ir
WORKDIR $INSTALL_DIR/deployment_tools
RUN rm -rf open_model_zoo
# clone forked branch
RUN git clone https://github.com/Ukhupacha/open_model_zoo.git
# build Inference Engine Samples
RUN $INSTALL_DIR/deployment_tools/inference_engine/samples/build_samples.sh
# build demo samples
RUN $INSTALL_DIR/deployment_tools/inference_engine/demos/build_demos.sh
CMD ["/bin/bash"]
phase3/buildcmd 100644 → 100755
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phase3/runcmd 100644 → 100755
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