feat: Docker images optimization

.dockerignore

@@ -0,0 +1,3 @@
+cpu.Dockerfile
+gpu.Dockerfile
+cpu-armv7.Dockerfile

.gitignore

@@ -1,4 +1,8 @@
-build/
+build/*
+!build/README.md
+!build/build.sh
+!build/get_models.sh
+!build/get_libs.sh
 model/
 models/
 clients/

.travis/build.sh

@@ -6,7 +6,7 @@ LOCAL_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
 ROOT_DIR=$(dirname "$LOCAL_DIR")
 cd "$ROOT_DIR"
 
-mkdir build
+mkdir -p build
 cd build
 
 # Configure

CMakeLists.txt

@@ -170,8 +170,10 @@ if (USE_CAFFE)
     if(USE_FAISS)
       if (NOT USE_CPU_ONLY AND CUDA_FOUND)
         string(REPLACE "/include" "" CUDA_PREFIX ${CUDA_INCLUDE_DIRS})
-        string(REPLACE "arch" "=arch" FAISS_NVCC_FLAGS ${NVCC_FLAGS_EXTRA})
-        set(CONFIGURE_OPTS --with-cuda=${CUDA_PREFIX} --with-cuda-arch="${FAISS_NVCC_FLAGS}")
+        if (NOT CUDA_ARCH)
+          string(REPLACE ";" " " CUDA_ARCH "${CUDA_NVCC_FLAGS}")
+        endif()
+        set(CONFIGURE_OPTS --with-cuda=${CUDA_PREFIX} --with-cuda-arch=${CUDA_ARCH})
         add_definitions(-DUSE_GPU_FAISS)
       else()
         set(CONFIGURE_OPTS "--without-cuda")
@@ -356,7 +358,6 @@ if (USE_CAFFE2)
     GIT_SUBMODULES ${PYTORCH_SUBMODULES}
     UPDATE_DISCONNECTED 1
     GIT_TAG ${PYTORCH_SUPPORTED_COMMIT}
-    GIT_CONFIG advice.detachedHead=false
     PATCH_COMMAND test -f ${PYTORCH_COMPLETE} && echo Skipping || echo cp modules/detectron/*_op.* caffe2/operators | bash && cp ${CAFFE2_OPS} caffe2/operators && git am ${PYTORCH_PATCHES}
     CONFIGURE_COMMAND test -f ${PYTORCH_COMPLETE} && echo Skipping || cmake ../pytorch ${PYTORCH_FLAGS}
     BUILD_COMMAND test -f ${PYTORCH_COMPLETE} && echo Skipping || make -j${N}
@@ -382,7 +383,6 @@ if (USE_CAFFE2)
     GIT_REPOSITORY https://github.com/facebookresearch/Detectron
     UPDATE_DISCONNECTED 1
     GIT_TAG ${DETECTRON_SUPPORTED_COMMIT}
-    GIT_CONFIG advice.detachedHead=false
     PATCH_COMMAND test -f ${DETECTRON_COMPLETE} && echo Skipping || git am ${DETECTRON_PATCHES}
     CONFIGURE_COMMAND ""
     BUILD_COMMAND ""
@@ -435,7 +435,7 @@ if (USE_TF)
       tensorflow_cc
       PREFIX tensorflow_cc
       INSTALL_DIR ${CMAKE_BINARY_DIR}
-      DOWNLOAD_COMMAND git clone https://github.com/FloopCZ/tensorflow_cc.git
+      DOWNLOAD_COMMAND git clone --branch v1.15.0 https://github.com/FloopCZ/tensorflow_cc.git
       CONFIGURE_COMMAND cd tensorflow_cc && mkdir -p build && cd build && cmake -DTENSORFLOW_STATIC=OFF -DTENSORFLOW_SHARED=ON .. && make && ln -s ${CMAKE_BINARY_DIR}/tensorflow_cc/src/tensorflow_cc/tensorflow_cc/build/tensorflow/tensorflow/contrib/makefile/gen/protobuf ${CMAKE_BINARY_DIR}/protobuf
       BUILD_COMMAND ""
       INSTALL_COMMAND ""
@@ -447,7 +447,7 @@ if (USE_TF)
       tensorflow_cc
       PREFIX tensorflow_cc
       INSTALL_DIR ${CMAKE_BINARY_DIR}
-      DOWNLOAD_COMMAND git clone https://github.com/FloopCZ/tensorflow_cc.git
+      DOWNLOAD_COMMAND git clone --branch v1.15.0 https://github.com/FloopCZ/tensorflow_cc.git
       CONFIGURE_COMMAND cd tensorflow_cc && mkdir -p build && cd build && cmake -DTENSORFLOW_STATIC=OFF -DTENSORFLOW_SHARED=ON -DALLOW_CUDA=OFF .. && make && ln -s ${CMAKE_BINARY_DIR}/tensorflow_cc/src/tensorflow_cc/tensorflow_cc/build/tensorflow/tensorflow/contrib/makefile/gen/protobuf ${CMAKE_BINARY_DIR}/protobuf
       BUILD_COMMAND ""
       INSTALL_COMMAND ""

docker/README.md → build/README.md

@@ -1,4 +1,4 @@
-## DeepDetect Docker images
+# DeepDetect Docker images
 
 This repository contains the Dockerfiles for building the CPU and GPU images for deepdetect.
 
@@ -10,7 +10,7 @@ The docker images contain:
 
 This allows to run the container and set an image classification model based on deep (residual) nets in two short command line calls.
 
-### Getting and running official images
+## Getting and running official images
 
 ```
 docker pull jolibrain/deepdetect_cpu
@@ -20,7 +20,7 @@ or
 docker pull jolibrain/deepdetect_gpu
 ```
 
-#### Running the CPU image
+### Running the CPU image
 
 ```
 docker run -d -p 8080:8080 jolibrain/deepdetect_cpu
@@ -48,7 +48,7 @@ curl -X POST "http://localhost:8080/predict" -d "{\"service\":\"imageserv\",\"pa
 {"status":{"code":200,"msg":"OK"},"head":{"method":"/predict","time":852.0,"service":"imageserv"},"body":{"predictions":{"uri":"http://i.ytimg.com/vi/0vxOhd4qlnA/maxresdefault.jpg","classes":[{"prob":0.2255125343799591,"cat":"n03868863 oxygen mask"},{"prob":0.20917612314224244,"cat":"n03127747 crash helmet"},{"last":true,"prob":0.07399296760559082,"cat":"n03379051 football helmet"}]}}}
 ```
 
-#### Running the GPU image
+### Running the GPU image
 
 This requires [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) in order for the local GPUs to be made accessible by the container.
 
@@ -75,7 +75,7 @@ curl -X POST "http://localhost:8080/predict" -d "{\"service\":\"imageserv\",\"pa
 
 Try the `POST` call twice: first time loads the net so it takes slightly below a second, then second call should yield a `time` around 100ms as reported in the output JSON.
 
-#### Access to server logs
+### Access to server logs
 
 To look at server logs, use 
 ```
@@ -112,10 +112,92 @@ docker run -d -p 8080:8080 -v /path/to/volume:/mnt jolibrain/deepdetect_cpu
 ```
 where `path/to/volume` is the path to your local volume that you'd like to attach to `/opt/deepdetect/`. This is useful for sharing / saving models, etc...
 
-#### Building an image
+## Build Deepdetect Docker images
 
-Example goes with the CPU image:
+Dockerfiles are presents on project root folder.
+
+We choose to prefix Dockerfiles with target architecture :
+* cpu-armv7.Dockerfile
+* cpu.Dockerfile
+* gpu.Dockerfile
+
+### Build script 
+
+Build script is avaliable in docker path : build/build.sh
+
+Docker build-arg : DEEPDETECT_BUILD
+
+Description : DEEPDETECT_BUILD build argument change cmake arguments in build.sh script.
+
+Expected values :
+
+* CPU
+  * caffe-tf
+  * default
+* GPU
+  * tf
+  * tf-cpu
+  * caffe-cpu-tf
+  * caffe-tf
+  * caffe2
+  * p100
+  * volta
+  * volta-faiss
+  * faiss
+  * default
+
+#### Launch build with environments variables
+
+```bash
+DEEPDETECT_ARCH=cpu,gpu DEEPDETECT_BUILD=default,caffe-tf,armv7,[...] ./build.sh
+```
+
+#### Launch build with build script parameters
+
+```bash
+Params usage: ./build.sh [options...]
+
+   -a, --deepdetect-arch          Choose Deepdetect architecture : cpu,gpu
+   -b, --deepdetect-build         Choose Deepdetect build profile : CPU (default,caffe-tf,armv7) / GPU (default,caffe-cpu-tf,caffe-tf,caffe2,p100,volta)
+```
+
+### Building an image
+
+#### Docker build arguments
+
+* DEEPDETECT_BUILD : Change cmake arguments, checkout build script documentation.
+* DEEPDETECT_DEFAULT_MODELS : [**true**/false] Enable or disable default models in deepdetect docker image. Default models size is about 160MB.
+
+#### Build examples
+
+Example with CPU image:
 ```
-cd cpu
-docker build -t jolibrain/deepdetect_cpu --no-cache .
+# Build with default cmake 
+docker build -t jolibrain/deepdetect_cpu --no-cache -f cpu.Dockerfile .
+
+# Build with default cmake and without default models
+docker build --build-arg DEEPDETECT_DEFAULT_MODELS=false -t jolibrain/deepdetect_cpu --no-cache -f cpu.Dockerfile .
+
+# Build with custom cmake
+docker build --build-arg DEEPDETECT_BUILD=caffe-tf -t jolibrain/deepdetect_cpu --no-cache -f cpu.Dockerfile .
+
 ```
+
+Example with CPU (armv7) image:
+```
+# Build with default cmake 
+docker build -t jolibrain/deepdetect_cpu:armv7 --no-cache -f cpu-armv7.Dockerfile .
+
+```
+
+Example with GPU image:
+```
+# Build with default cmake 
+docker build -t jolibrain/deepdetect_gpu --no-cache -f gpu.Dockerfile .
+
+# Build with default cmake and without default models
+docker build --build-arg DEEPDETECT_DEFAULT_MODELS=false -t jolibrain/deepdetect_gpu --no-cache -f gpu.Dockerfile .
+
+# Build with custom cmake
+docker build --build-arg DEEPDETECT_BUILD=caffe-tf -t jolibrain/deepdetect_gpu --no-cache -f gpu.Dockerfile .
+```