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README.md

DeepDetect Docker images

Installation

See https://github.com/jolibrain/deepdetect/tree/master/docs/docker.md

Build

Dockerfiles are stored in the "docker" folder, but you must launch build from root directory.

We choose to prefix Dockerfiles with target architecture :

  • cpu.Dockerfile
  • cpu-armv7.Dockerfile
  • gpu.Dockerfile

Build script

Build script is available 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
    • tf
    • torch
    • default
  • GPU
    • tf
    • tf-cpu
    • caffe-cpu-tf
    • caffe-tf
    • torch
    • default

Prepare build environment

Create build directory and put build script inside :

mkdir build
cd build
cp -a ../build.sh .

Launch build with environments variables

DEEPDETECT_ARCH=cpu,gpu DEEPDETECT_BUILD=default,caffe-tf,armv7,[...] ./build.sh

Launch build with build script parameters

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.
  • DEEPDETECT_GPU_VARIANT : [default/legacy61] GPU-only arch preset. Today, both variants track the current Dockerfile CUDA line and support compute capability 6.1+. Compute capability 12.1 is enabled only for DEEPDETECT_BUILD=tensorrt. legacy61 is kept as a compatibility alias so the later CUDA 13 split can happen without changing the interface.
  • DD_CUDA_VERSION / DD_CUDA_MAJOR_MINOR : Optional CUDA image overrides if you want to test another CUDA image explicitly.

Build examples

You must launch build from root directory

Example with CPU image:

# Build with default cmake
export DOCKER_BUILDKIT=1
docker build -t jolibrain/deepdetect_cpu --no-cache -f docker/cpu.Dockerfile .

# Build with default cmake and without default models
export DOCKER_BUILDKIT=1
docker build --build-arg DEEPDETECT_DEFAULT_MODELS=false -t jolibrain/deepdetect_cpu --no-cache -f cpu.Dockerfile .

# Build with custom cmake
export DOCKER_BUILDKIT=1
docker build --build-arg DEEPDETECT_BUILD=caffe-tf -t jolibrain/deepdetect_cpu --no-cache -f docker/cpu.Dockerfile .

Example with CPU (armv7) image:

# Build with default cmake
export DOCKER_BUILDKIT=1
docker build -t jolibrain/deepdetect_cpu:armv7 --no-cache -f docker/cpu-armv7.Dockerfile .

Example with GPU image:

# Build with default cmake
export DOCKER_BUILDKIT=1
docker build -t jolibrain/deepdetect_gpu --no-cache -f docker/gpu.Dockerfile .

# Build with default cmake and without default models
export DOCKER_BUILDKIT=1
docker build --build-arg DEEPDETECT_DEFAULT_MODELS=false -t jolibrain/deepdetect_gpu --no-cache -f docker/gpu.Dockerfile .

# Build with custom cmake
export DOCKER_BUILDKIT=1
docker build --build-arg DEEPDETECT_BUILD=caffe-tf -t jolibrain/deepdetect_gpu --no-cache -f docker/gpu.Dockerfile .

# Build the legacy61 compatibility alias
export DOCKER_BUILDKIT=1
docker build \
  --build-arg DEEPDETECT_GPU_VARIANT=legacy61 \
  -t jolibrain/deepdetect_gpu:legacy61 \
  --no-cache \
  -f docker/gpu.Dockerfile .

# Same legacy61 build through the helper wrapper
export DOCKER_BUILDKIT=1
./docker/build_gpu_image.sh legacy61 -t jolibrain/deepdetect_gpu:legacy61 --no-cache