diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml
index 98428a4733..6ece3f59a8 100644
--- a/.github/workflows/docker.yml
+++ b/.github/workflows/docker.yml
@@ -12,9 +12,9 @@ jobs:
steps:
- uses: actions/checkout@v3
- name: Build docker image
- run: docker build . -t doctr-tf-py3.8-slim
+ run: docker build -t doctr-tf-py3.8-slim --build-arg SYSTEM=cpu .
- name: Run docker container
- run: docker run doctr-tf-py3.8-slim python -c 'import doctr'
+ run: docker run doctr-tf-py3.8-slim python3 -c 'import doctr'
pytest-api:
runs-on: ${{ matrix.os }}
diff --git a/.github/workflows/public_docker_images.yml b/.github/workflows/public_docker_images.yml
new file mode 100644
index 0000000000..de77d1a265
--- /dev/null
+++ b/.github/workflows/public_docker_images.yml
@@ -0,0 +1,86 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+#
+name: Docker image on ghcr.io
+
+on:
+ push:
+ tags:
+ - 'v*'
+ pull_request:
+ branches: main
+ schedule:
+ - cron: '0 2 29 * *' # At 02:00 on day-of-month 29
+
+env:
+ REGISTRY: ghcr.io
+
+jobs:
+ build-and-push-image:
+ runs-on: ubuntu-latest
+
+ strategy:
+ fail-fast: false
+ matrix:
+ # Must match version at https://www.python.org/ftp/python/
+ python: ["3.8.18", "3.9.18", "3.10.13"]
+ framework: ["tf", "torch"]
+ system: ["cpu", "gpu"]
+
+ # Sets the permissions granted to the `GITHUB_TOKEN` for the actions in this job.
+ permissions:
+ contents: read
+ packages: write
+
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v4
+
+ - name: Log in to the Container registry
+ uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1
+ with:
+ registry: ${{ env.REGISTRY }}
+ username: ${{ github.actor }}
+ password: ${{ secrets.GITHUB_TOKEN }}
+
+ - name: Extract metadata (tags, labels) for Docker
+ id: meta
+ uses: docker/metadata-action@9ec57ed1fcdbf14dcef7dfbe97b2010124a938b7
+ with:
+ images: ${{ env.REGISTRY }}/${{ github.repository }}
+ tags: |
+ # used only on schedule event
+ type=schedule,pattern={{date 'YYYY-MM'}},prefix=${{ matrix.framework }}-py${{ matrix.python }}-${{ matrix.system }}-
+ # used only if a tag following semver is published
+ type=semver,pattern={{raw}},prefix=${{ matrix.framework }}-py${{ matrix.python }}-${{ matrix.system }}-
+
+ - name: Build Docker image
+ id: build
+ uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4
+ with:
+ context: .
+ build-args: |
+ FRAMEWORK=${{ matrix.framework }}
+ PYTHON_VERSION=${{ matrix.python }}
+ SYSTEM=${{ matrix.system }}
+ DOCTR_REPO=${{ github.repository }}
+ DOCTR_VERSION=${{ github.sha }}
+ push: false # push only if `import doctr` works
+ tags: ${{ steps.meta.outputs.tags }}
+
+ - name: Check if `import doctr` works
+ run: docker run ${{ steps.build.outputs.imageid }} python3 -c 'import doctr'
+
+ - name: Push Docker image
+ # Push only if the CI is not triggered by "PR on main"
+ if: github.ref == 'refs/heads/main' && github.event_name != 'pull_request'
+ uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4
+ with:
+ context: .
+ build-args: |
+ FRAMEWORK=${{ matrix.framework }}
+ PYTHON_VERSION=${{ matrix.python }}
+ SYSTEM=${{ matrix.system }}
+ DOCTR_REPO=${{ github.repository }}
+ DOCTR_VERSION=${{ github.sha }}
+ push: true
+ tags: ${{ steps.meta.outputs.tags }}
diff --git a/Dockerfile b/Dockerfile
index badf6e5fda..dfde03233f 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,21 +1,72 @@
-# Use the TensorFlow GPU image as the base image. This image also works with CPU-only setups
-FROM tensorflow/tensorflow@sha256:b4676741c491bff3d0f29c38c369281792c7d5c5bfa2b1aa93e5231a8d236323
+FROM ubuntu:22.04
-ENV PYTHONUNBUFFERED=1
-ENV PYTHONDONTWRITEBYTECODE=1
-ENV DOCTR_CACHE_DIR=/app/.cache
+ENV DEBIAN_FRONTEND=noninteractive
+ENV LANG=C.UTF-8
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
-WORKDIR /app
+ARG SYSTEM=gpu
-COPY . .
+# Enroll NVIDIA GPG public key and install CUDA
+RUN if [ "$SYSTEM" = "gpu" ]; then \
+ apt-get update && \
+ apt-get install -y gnupg ca-certificates wget && \
+ # - Install Nvidia repo keys
+ # - See: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#network-repo-installation-for-ubuntu
+ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
+ dpkg -i cuda-keyring_1.1-1_all.deb && \
+ apt-get update && apt-get install -y --no-install-recommends \
+ cuda-command-line-tools-11-8 \
+ cuda-cudart-dev-11-8 \
+ cuda-nvcc-11-8 \
+ cuda-cupti-11-8 \
+ cuda-nvprune-11-8 \
+ cuda-libraries-11-8 \
+ cuda-nvrtc-11-8 \
+ libcufft-11-8 \
+ libcurand-11-8 \
+ libcusolver-11-8 \
+ libcusparse-11-8 \
+ libcublas-11-8 \
+ # - CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
+ libcudnn8=8.6.0.163-1+cuda11.8 \
+ libnvinfer-plugin8=8.6.1.6-1+cuda11.8 \
+ libnvinfer8=8.6.1.6-1+cuda11.8; \
+fi
-# Install necessary dependencies for video processing and GUI operations
-RUN apt-get update \
- && apt-get install --no-install-recommends ffmpeg libsm6 libxext6 -y \
- && apt-get autoremove -y \
- && rm -rf /var/lib/apt/lists/*
+RUN apt-get update && apt-get install -y --no-install-recommends \
+ # - Other packages
+ build-essential \
+ pkg-config \
+ curl \
+ wget \
+ software-properties-common \
+ unzip \
+ git \
+ # - Packages to build Python
+ tar make gcc zlib1g-dev libffi-dev libssl-dev liblzma-dev libbz2-dev \
+ # - Packages for docTR
+ libgl1-mesa-dev libsm6 libxext6 libxrender-dev libpangocairo-1.0-0 \
+ && apt-get clean \
+ && rm -rf /var/lib/apt/lists/* \
+fi
-# Install the current application with TensorFlow extras and modify permissions
-RUN pip install --upgrade pip setuptools wheel \
- && pip install -e .[tf] \
- && chmod -R a+w /app
+# Install Python
+ARG PYTHON_VERSION=3.10.13
+
+RUN wget http://www.python.org/ftp/python/$PYTHON_VERSION/Python-$PYTHON_VERSION.tgz && \
+ tar -zxf Python-$PYTHON_VERSION.tgz && \
+ cd Python-$PYTHON_VERSION && \
+ mkdir /opt/python/ && \
+ ./configure --prefix=/opt/python && \
+ make && \
+ make install
+
+ENV PATH=/opt/python/bin:$PATH
+
+# Install docTR
+ARG FRAMEWORK=tf
+ARG DOCTR_REPO='mindee/doctr'
+ARG DOCTR_VERSION=main
+RUN pip3 install -U pip setuptools wheel && \
+ pip3 install "python-doctr[$FRAMEWORK]@git+https://github.com/$DOCTR_REPO.git@$DOCTR_VERSION"
diff --git a/README.md b/README.md
index ea5ec082d7..940c4a4a8b 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
-[](https://slack.mindee.com) [](LICENSE)  [](https://codecov.io/gh/mindee/doctr) [](https://www.codefactor.io/repository/github/mindee/doctr) [](https://app.codacy.com/gh/mindee/doctr?utm_source=github.com&utm_medium=referral&utm_content=mindee/doctr&utm_campaign=Badge_Grade) [](https://mindee.github.io/doctr) [](https://pypi.org/project/python-doctr/) [](https://huggingface.co/spaces/mindee/doctr) [](https://colab.research.google.com/github/mindee/notebooks/blob/main/doctr/quicktour.ipynb)
+[](https://slack.mindee.com) [](LICENSE)  [](https://github.com/mindee.doctr/packages) [](https://codecov.io/gh/mindee/doctr) [](https://www.codefactor.io/repository/github/mindee/doctr) [](https://app.codacy.com/gh/mindee/doctr?utm_source=github.com&utm_medium=referral&utm_content=mindee/doctr&utm_campaign=Badge_Grade) [](https://mindee.github.io/doctr) [](https://pypi.org/project/python-doctr/) [](https://huggingface.co/spaces/mindee/doctr) [](https://colab.research.google.com/github/mindee/notebooks/blob/main/doctr/quicktour.ipynb)
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
@@ -260,10 +260,50 @@ Check out our [TensorFlow.js demo](https://github.com/mindee/doctr-tfjs-demo) to
### Docker container
-If you wish to deploy containerized environments, you can use the provided Dockerfile to build a docker image:
+[We offers Docker container support for easy testing and deployment](https://github.com/mindee/doctr/packages).
+
+#### Using GPU with docTR Docker Images
+
+The docTR Docker images are GPU-ready and based on CUDA `11.8`.
+However, to use GPU support with these Docker images, please ensure that Docker is configured to use your GPU.
+
+To verify and configure GPU support for Docker, please follow the instructions provided in the [NVIDIA Container Toolkit Installation Guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html).
+
+Once Docker is configured to use GPUs, you can run docTR Docker containers with GPU support:
+
+```shell
+docker run --it --gpus all ghcr.io/mindee/doctr:tf-py3.8.18-gpu-2023-09 bash
+```
+
+#### Available Tags
+
+The Docker images for docTR follow a specific tag nomenclature: `-py--`. Here's a breakdown of the tag structure:
+
+- ``: `tf` (TensorFlow) or `torch` (PyTorch).
+- ``: `3.8.18`, `3.9.18`, or `3.10.13`.
+- ``: `cpu` or `gpu`
+- ``: a tag >= `v0.7.1`
+- ``: e.g. `2023-09`
+
+Here are examples of different image tags:
+
+| Tag | Description |
+|----------------------------|---------------------------------------------------|
+| `tf-py3.8.18-cpu-v0.7.1` | TensorFlow version `3.8.18` with docTR `v0.7.1`. |
+| `torch-py3.9.18-gpu-2023-09`| PyTorch version `3.9.18` with GPU support and a monthly build from `2023-09`. |
+
+#### Building Docker Images Locally
+
+You can also build docTR Docker images locally on your computer.
+
+```shell
+docker build -t doctr .
+```
+
+You can specify custom Python versions and docTR versions using build arguments. For example, to build a docTR image with TensorFlow, Python version `3.9.10`, and docTR version `v0.7.0`, run the following command:
```shell
-docker build . -t
+docker build -t doctr --build-arg FRAMEWORK=tf --build-arg PYTHON_VERSION=3.9.10 --build-arg DOCTR_VERSION=v0.7.0 .
```
### Example script