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136 lines
5.6 KiB
136 lines
5.6 KiB
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# #==========================================================================
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FROM tensorflow/tensorflow:nightly-devel
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# Get the tensorflow models research directory, and move it into tensorflow
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# source folder to match recommendation of installation
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RUN git clone --depth 1 https://github.com/tensorflow/models.git && \
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mv models /tensorflow/models
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# Install gcloud and gsutil commands
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# https://cloud.google.com/sdk/docs/quickstart-debian-ubuntu
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RUN export CLOUD_SDK_REPO="cloud-sdk-$(lsb_release -c -s)" && \
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echo "deb http://packages.cloud.google.com/apt $CLOUD_SDK_REPO main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list && \
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curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - && \
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apt-get update -y && apt-get install google-cloud-sdk -y
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# Install the Tensorflow Object Detection API from here
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# https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md
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# Install object detection api dependencies
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RUN apt-get install -y protobuf-compiler python-pil python-lxml python-tk && \
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pip install Cython && \
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pip install contextlib2 && \
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pip install jupyter && \
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pip install matplotlib
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# Install pycocoapi
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RUN git clone --depth 1 https://github.com/cocodataset/cocoapi.git && \
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cd cocoapi/PythonAPI && \
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make -j8 && \
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cp -r pycocotools /tensorflow/models/research && \
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cd ../../ && \
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rm -rf cocoapi
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# Get protoc 3.0.0, rather than the old version already in the container
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RUN curl -OL "https://github.com/google/protobuf/releases/download/v3.0.0/protoc-3.0.0-linux-x86_64.zip" && \
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unzip protoc-3.0.0-linux-x86_64.zip -d proto3 && \
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mv proto3/bin/* /usr/local/bin && \
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mv proto3/include/* /usr/local/include && \
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rm -rf proto3 protoc-3.0.0-linux-x86_64.zip
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# Run protoc on the object detection repo
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RUN cd /tensorflow/models/research && \
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protoc object_detection/protos/*.proto --python_out=.
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# Set the PYTHONPATH to finish installing the API
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ENV PYTHONPATH $PYTHONPATH:/tensorflow/models/research:/tensorflow/models/research/slim
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# Install wget (to make life easier below) and editors (to allow people to edit
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# the files inside the container)
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RUN apt-get install -y wget vim emacs nano
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# Grab various data files which are used throughout the demo: dataset,
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# pretrained model, and pretrained TensorFlow Lite model. Install these all in
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# the same directories as recommended by the blog post.
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# Pets example dataset
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RUN mkdir -p /tmp/pet_faces_tfrecord/ && \
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cd /tmp/pet_faces_tfrecord && \
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curl "http://download.tensorflow.org/models/object_detection/pet_faces_tfrecord.tar.gz" | tar xzf -
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# Pretrained model
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# This one doesn't need its own directory, since it comes in a folder.
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RUN cd /tmp && \
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curl -O "http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_0.75_depth_300x300_coco14_sync_2018_07_03.tar.gz" && \
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tar xzf ssd_mobilenet_v1_0.75_depth_300x300_coco14_sync_2018_07_03.tar.gz && \
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rm ssd_mobilenet_v1_0.75_depth_300x300_coco14_sync_2018_07_03.tar.gz
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# Trained TensorFlow Lite model. This should get replaced by one generated from
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# export_tflite_ssd_graph.py when that command is called.
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RUN cd /tmp && \
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curl -L -o tflite.zip \
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https://storage.googleapis.com/download.tensorflow.org/models/tflite/frozengraphs_ssd_mobilenet_v1_0.75_quant_pets_2018_06_29.zip && \
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unzip tflite.zip -d tflite && \
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rm tflite.zip
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# Install Android development tools
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# Inspired by the following sources:
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# https://github.com/bitrise-docker/android/blob/master/Dockerfile
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# https://github.com/reddit/docker-android-build/blob/master/Dockerfile
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# Set environment variables
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ENV ANDROID_HOME /opt/android-sdk-linux
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ENV ANDROID_NDK_HOME /opt/android-ndk-r14b
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ENV PATH ${PATH}:${ANDROID_HOME}/tools:${ANDROID_HOME}/tools/bin:${ANDROID_HOME}/platform-tools
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# Install SDK tools
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RUN cd /opt && \
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curl -OL https://dl.google.com/android/repository/sdk-tools-linux-4333796.zip && \
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unzip sdk-tools-linux-4333796.zip -d ${ANDROID_HOME} && \
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rm sdk-tools-linux-4333796.zip
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# Accept licenses before installing components, no need to echo y for each component
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# License is valid for all the standard components in versions installed from this file
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# Non-standard components: MIPS system images, preview versions, GDK (Google Glass) and Android Google TV require separate licenses, not accepted there
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RUN yes | sdkmanager --licenses
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# Install platform tools, SDK platform, and other build tools
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RUN yes | sdkmanager \
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"tools" \
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"platform-tools" \
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"platforms;android-27" \
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"platforms;android-23" \
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"build-tools;27.0.3" \
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"build-tools;23.0.3"
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# Install Android NDK (r14b)
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RUN cd /opt && \
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curl -L -o android-ndk.zip http://dl.google.com/android/repository/android-ndk-r14b-linux-x86_64.zip && \
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unzip -q android-ndk.zip && \
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rm -f android-ndk.zip
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# Configure the build to use the things we just downloaded
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RUN cd /tensorflow && \
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printf '\n\nn\ny\nn\nn\nn\ny\nn\nn\nn\nn\nn\nn\n\ny\n%s\n\n\n' ${ANDROID_HOME}|./configure
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WORKDIR /tensorflow
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