Update with OpenVINO 2020.1.023

19313051 · Ukhu · 91962e9f · 19313051 · 19313051 · 19313051
Commit 19313051 authored Mar 11, 2020 by Ukhu
--- a/.gitignore
+++ b/.gitignore
 *.tgz
-*.mp4
 *.pb
 .idea*
--- a/debug/Dockerfile
+++ b/debug/Dockerfile
@@ -5,9 +5,8 @@ FROM local/dockervino:phase1 as phase1
 MAINTAINER jdg:juan-diego.gonzales-zuniga@kontron.com
 # Copy models from phase2
 COPY --from=phase2 /root/openvino_models/ir /root/openvino_models/ir
-ARG INSTALL_DIR=/opt/intel/openvino
 WORKDIR $INSTALL_DIR/deployment_tools
-RUN apt install -y x11-utils vim strace wget libtool autoconf unzip libmosquittopp-dev
+RUN apt install -y x11-utils vim strace libtool autoconf libmosquittopp-dev mosquitto mosquitto-clients
 WORKDIR /tmp
 RUN wget https://github.com/libusb/libusb/archive/v1.0.22.zip && \
   unzip v1.0.22.zip && cd libusb-1.0.22 && \

--- a/debug/runcmd
+++ b/debug/runcmd
@@ -25,7 +25,7 @@ examples_dir=/root/omz_demos_build/intel64/Release
 models_dir=/root/openvino_models/ir
 build_cmd=/opt/intel/openvino/deployment_tools/open_model_zoo/demos/build_demos.sh
 # Input: IPCam or USBCam
-input=https://motchallenge.net/movies/ETH-Bahnhof.mp4
+input=/videos/test.mp4
 #################################
 ########    Examples  ###########
 #################################
@@ -51,7 +51,7 @@ docker run $opts \
  -d \
  -ti \
  --mount type=bind,source="$(pwd)"/../../open_model_zoo,target=/opt/intel/openvino/deployment_tools/open_model_zoo \
-  --mount type=bind,source="$(pwd)"/videos,target=/videos \
+  --mount type=bind,source="$(pwd)"/../demo/videos,target=/videos \
  --privileged \
  --net=host \
  --env="setupvars=$setupvars" \

--- a/demo/Dockerfile
+++ b/demo/Dockerfile
 FROM local/dockervino:phase2 as phase2
 FROM local/dockervino:phase1 as phase1
-ARG INSTALL_DIR=/opt/intel/openvino
 WORKDIR $INSTALL_DIR/deployment_tools
 RUN apt install -y libmosquittopp-dev && \
 	rm -rf open_model_zoo && \

--- a/demo/openpose
+++ b/demo/openpose
+#!/bin/bash
+myimage=local/dockervino:demo
+myname=dockervinodemo
+
+#################################
+##### Display Parameters #####
+#################################
+# if run from a graphics window or shell, set some server params, else document what is needed
+[ k$DISPLAY = k ] && doit=echo
+# X11 Display and access file (to us in XAUTORITY env)
+# enable access from anywhere (used for containers)
+$doit xhost +
+# disable screen saver
+$doit xset s 0
+# force screen to use (0 is usually the physical display of the system, others would be Xvnc virtual screens)
+display=$DISPLAY
+rm -f ./xauthority ; cp $XAUTHORITY ./xauthority ;chmod 666 ./xauthority #else root user inside container cannot open
+
+#################################
+#####  General Parameters  ######
+#################################
+# Init Openvino environment
+setupvars=/opt/intel/openvino/bin/setupvars.sh
+examples_dir=/root/omz_demos_build/intel64/Release
+models_dir=/root/openvino_models/ir
+# Input: IPCam or USBCam
+input=/videos/test.mp4
+
+#################################
+########    Examples  ###########
+#################################
+
+####### CPU Pose Estimation ########
+device=CPU
+app=${examples_dir}/human_pose_estimation_demo
+model=${models_dir}/intel/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml
+raw=true
+broker=kontron-lora.cloudapp.net
+client=Demo
+
+
+###### NCS2 Pose Estimation  ######
+#device=MYRIAD
+#app=${examples_dir}/human_pose_estimation_demo
+#model=${models_dir}/intel/human-pose-estimation-0001/FP16/human-pose-estimation-0001.xml
+
+
+opts="--entrypoint=/entrypoint.sh"
+
+# Running the container
+set -x
+docker run $opts \
+  -d \
+  -ti \
+  --mount type=bind,source="$(pwd)"/videos,target=/videos \
+  --privileged \
+  --net=host \
+  --env="setupvars=$setupvars" \
+  --env="DISPLAY=$display" \
+  --env="input=$input" \
+  --env="device=$device" \
+  --env="app=$app" \
+  --env="model=$model" \
+  --env="m_det=$m_det" \
+  --env="m_reid=$m_reid" \
+  --env="broker=$broker" \
+  --env="client=$client" \
+  --env="raw=$raw" \
+  --env="agM=$agM" \
+  --env="emM=$emM" \
+  --env="hpM=$hpM" \
+  --device="/dev/video0:/dev/video0" \
+  --volume="/dev:/dev" \
+  --volume="/tmp/.X11-unix:/tmp/.X11-unix" \
+  --env="PS1=$myname> "\
+  --publish-all=true \
+  --hostname=$myname \
+  --entrypoint /entrypoint.sh \
+  --name $myname \
+  --cidfile=/tmp/monitcont.id \
+        $myimage /bin/sh
+        contid=$(cat /tmp/monitcont.id; rm -f /tmp/monitcont.id)
+set +x
+        $debug docker logs $contid
+        $debug docker inspect --format='{{range $p, $conf := .NetworkSettings.Ports}} {{$p}} -> {{(index $conf 0).HostPort}} {{end}}' $1 $contid
+set +x
--- a/demo/runcmd
+++ b/demo/runcmd
@@ -24,20 +24,12 @@ 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=https://motchallenge.net/movies/ETH-Bahnhof.mp4
+input=/videos/test.mp4

 #################################
 ########    Examples  ###########
 #################################

-####### CPU Pose Estimation ########
-#device=CPU
-#app=${examples_dir}/human_pose_estimation_demo
-#model=${models_dir}/intel/human-pose-estimation-0001/FP32/human-pose-estimation-0001.xml
-#raw=true
-#broker=kontron-lora.cloudapp.net
-#client=Demo
-
 ####### Pedestrian Tracker  ########
 device=CPU
 app=${examples_dir}/pedestrian_tracker_demo
@@ -59,6 +51,7 @@ set -x
 docker run $opts \
  -d \
  -ti \
+  --mount type=bind,source="$(pwd)"/videos,target=/videos \
  --privileged \
  --net=host \
  --env="setupvars=$setupvars" \

--- a/demo/videos/test.mp4
+++ b/demo/videos/test.mp4
--- a/phase1/Dockerfile
+++ b/phase1/Dockerfile
@@ -2,49 +2,52 @@
 # Replace openvinoTar with the openvinoversion
 # The openvinoTar is erased after installation 

-FROM ubuntu:xenial
+FROM ubuntu:18.04
 MAINTAINER jdg:juan-diego.gonzales-zuniga@kontron.com
-ARG openvinoTar=l_openvino_toolkit_p_2019.3.376
-ARG INSTALL_DIR=/opt/intel/openvino
+# Dependencies
+ARG DEPENDENCIES="autoconf \
+		  automake \
+		  build-essential \
+		  cmake \
+		  cpio \
+		  curl \
+		  gnupg2 \
+		  libdrm2 \
+		  libglib2.0-0 \
+		  lsb-release \
+		  libgtk-3-0 \
+		  libtool \
+		  python3-pip \
+		  udev \
+		  unzip \
+		  sudo \
+		  wget \
+		  git"
+
+RUN apt-get update && apt-get -y upgrade && apt-get autoremove && \ 
+    apt-get install -y --no-install-recommends ${DEPENDENCIES} && \
+    rm -rf /var/lib/apt/lists/*
+
+# Openvino Version
+ARG openvinoTar=l_openvino_toolkit_p_2020.1.023
+ENV INSTALL_DIR=/opt/intel/openvino
 ARG TEMP_DIR=/tmp/openvino_installer
 RUN mkdir -p $TEMP_DIR
 WORKDIR $TEMP_DIR 
 COPY ./$openvinoTar.tgz $TEMP_DIR
-RUN apt-get update && apt-get -y upgrade && apt-get autoremove
-
-# installing needed dependencies
-RUN apt-get install -y --no-install-recommends \
-	build-essential \
-	cpio \
-	wget \
-	git \
-	curl \
-	lsb-release \
-	pciutils \
-	software-properties-common \
-	sudo && \
-	sudo add-apt-repository ppa:jonathonf/python-3.6 && \
-	apt-get update && apt-get install -y python3.6 python3.6-dev && \
-	curl https://bootstrap.pypa.io/get-pip.py | sudo -H python3.6 && \
-	rm /usr/bin/python3 && \
-	sudo ln -s python3.6 /usr/bin/python3 && \
-	pip3 install pillow && \
-	rm -rf /var/lib/apt/lists/*
-# installing openVINO itself
 RUN tar xf $openvinoTar.tgz && cd $openvinoTar && \
 	sed -i 's/decline/accept/g' silent.cfg && \
 	./install.sh -s silent.cfg && \
-	rm -rf $TEMP_DIR
-
-# installing openVINO dependencies
-RUN bash $INSTALL_DIR/install_dependencies/install_openvino_dependencies.sh
+	rm -rf $TEMP_DIR && \
+	$INSTALL_DIR/install_dependencies/install_openvino_dependencies.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
+# Install model_optimizer requisites, it  needs tf 1.5 for ApolloLake and setuptools
+RUN sed -i 's/<2.0.0/<=1.5.0/g' $INSTALL_DIR/deployment_tools/model_optimizer/requirements.txt
+RUN pip3 install setuptools
 RUN $INSTALL_DIR/deployment_tools/model_optimizer/install_prerequisites/install_prerequisites.sh

-# init openvino env
+# Init Openvino variables
 RUN echo "source $INSTALL_DIR/bin/setupvars.sh" >> /root/.bashrc
-# check installation with example
+# Check installation with benchmark demo
 RUN $INSTALL_DIR/deployment_tools/demo/demo_benchmark_app.sh
 CMD ["/bin/bash"]
--- a/phase2/Dockerfile
+++ b/phase2/Dockerfile
@@ -3,22 +3,9 @@

 FROM local/dockervino:phase1
 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 $models/ir/ssd300/FP16 --model_name ssd300 --data_type FP16
+ENV downloader=$INSTALL_DIR/deployment_tools/tools/model_downloader/downloader.py
+ENV optimizer=$INSTALL_DIR/deployment_tools/model_optimizer
+ENV models=/root/openvino_models

 # Downloading Human Pose Detection
 RUN python3 $downloader --name human-pose-estimation-0001 --output_dir $models/ir
@@ -35,54 +22,44 @@ RUN python3 $downloader --name emotions-recognition-retail-0003 --output_dir $mo
 # 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
+# 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
+
+# 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
+
+# Download Yolo v3
+WORKDIR $models 
+RUN apt-get install git wget -y
+RUN wget https://download.01.org/opencv/public_models/022020/yolo_v3/yolov3.pb && \
+    wget https://download.01.org/opencv/public_models/022020/yolo_v3/yolo_v3_new.json

 # 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_model yolov3.pb \
+	--transformations_config yolo_v3_new.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_model yolov3.pb \
+	--transformations_config yolo_v3_new.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
@@ -90,19 +67,17 @@ 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 \
+	--transformations_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 \
+        --transformations_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"]
--- a/phase2/yolo_v3.json
+++ b/phase2/yolo_v3.json
-[
-  {
-    "id": "TFYOLOV3",
-    "match_kind": "general",
-    "custom_attributes": {
-      "classes": 80,
-      "coords": 4,
-      "num": 9,
-      "mask": [0, 1, 2],
-      "jitter": 0.3,
-      "ignore_thresh": 0.7,
-      "truth_thresh": 1,
-      "random": 1,
-      "anchors":[10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59,119, 116,90, 156, 198, 373, 326],
-      "entry_points": ["detector/yolo-v3/Reshape", "detector/yolo-v3/Reshape_4", "detector/yolo-v3/Reshape_8"]
-    }
-  }
-]
--- a/phase2/yolo_v3_tiny.json
+++ b/phase2/yolo_v3_tiny.json
-[
-  {
-    "id": "TFYOLOV3",
-    "match_kind": "general",
-    "custom_attributes": {
-      "classes": 80,
-      "coords": 4,
-      "num": 6,
-      "mask": [0, 1, 2],
-      "jitter": 0.3,
-      "ignore_thresh": 0.7,
-      "truth_thresh": 1,
-      "random": 1,
-      "anchors":[10, 14, 23, 27, 37, 58, 81, 82, 135, 169, 344, 319],
-      "entry_points": ["detector/yolo-v3-tiny/Reshape", "detector/yolo-v3-tiny/Reshape_4"]
-    }
-  }
-]