[Docker] Add Dockerfile and corresponding CI job

.github/workflows/docker.yml

@@ -0,0 +1,83 @@
+# 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 1 6 *'  # At 02:00 on day-of-month 1 in June (once a year actually)
+
+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: ["3.10.13"]
+        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@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ${{ env.REGISTRY }}/${{ github.repository }}
+          tags: |
+            # used only on schedule event
+            type=schedule,pattern={{date 'YYYY-MM'}},prefix=OnnxTR-${{ matrix.system }}-py${{ matrix.python }}-
+            # used only if a tag following semver is published
+            type=semver,pattern={{raw}},prefix=OnnxTR-${{ matrix.system }}-py${{ matrix.python }}-
+
+      - name: Build Docker image
+        id: build
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          build-args: |
+            PYTHON_VERSION=${{ matrix.python }}
+            SYSTEM=${{ matrix.system }}
+            ONNXTR_REPO=${{ github.repository }}
+            ONNXTR_VERSION=${{ github.sha }}
+          push: false  # push only if `import onnxtr` works
+          tags: ${{ steps.meta.outputs.tags }}
+
+      - name: Check if `import onnxtr` works
+        run: docker run ${{ steps.build.outputs.imageid }} python3 -c 'import onnxtr; print(onnxtr.__version__)'
+
+      - name: Push Docker image
+        # Push only if the CI is not triggered by "PR on main"
+        if: github.ref == 'refs/heads/main' && github.event_name != 'pull_request'
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          build-args: |
+            PYTHON_VERSION=${{ matrix.python }}
+            SYSTEM=${{ matrix.system }}
+            ONNXTR_REPO=${{ github.repository }}
+            ONNXTR_VERSION=${{ github.sha }}
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}

Dockerfile

@@ -0,0 +1,76 @@
+FROM ubuntu:22.04
+
+ENV DEBIAN_FRONTEND=noninteractive
+ENV LANG=C.UTF-8
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
+ARG SYSTEM=gpu
+
+# Enroll NVIDIA GPG public key and install CUDA
+RUN if [ "$SYSTEM" = "gpu" ]; then \
+    apt-get update && \
+    apt-get install -y gnupg ca-certificates wget && \
+    # - Install Nvidia repo keys
+    # - See: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#network-repo-installation-for-ubuntu
+    wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
+    dpkg -i cuda-keyring_1.1-1_all.deb && \
+    apt-get update && apt-get install -y --no-install-recommends \
+    # NOTE: The following CUDA_VERSION, CUDNN_VERSION, and NVINFER_VERSION are for CUDA 11.8
+    # - this needs to match exactly with the host system otherwise the onnxruntime-gpu package isn't able to work correct. !!
+    cuda-command-line-tools-11-8 \
+    cuda-cudart-dev-11-8 \
+    cuda-nvcc-11-8 \
+    cuda-cupti-11-8 \
+    cuda-nvprune-11-8 \
+    cuda-libraries-11-8 \
+    cuda-nvrtc-11-8 \
+    libcufft-11-8 \
+    libcurand-11-8 \
+    libcusolver-11-8 \
+    libcusparse-11-8 \
+    libcublas-11-8 \
+    # - CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
+    libcudnn8=8.6.0.163-1+cuda11.8 \
+    libnvinfer-plugin8=8.6.1.6-1+cuda11.8 \
+    libnvinfer8=8.6.1.6-1+cuda11.8; \
+fi
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    # - Other packages
+    build-essential \
+    pkg-config \
+    curl \
+    wget \
+    software-properties-common \
+    unzip \
+    git \
+    # - Packages to build Python
+    tar make gcc zlib1g-dev libffi-dev libssl-dev liblzma-dev libbz2-dev libsqlite3-dev \
+    # - Packages for docTR
+    libgl1-mesa-dev libsm6 libxext6 libxrender-dev libpangocairo-1.0-0 \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/* \
+fi
+
+# Install Python
+ARG PYTHON_VERSION=3.10.13
+
+RUN wget http://www.python.org/ftp/python/$PYTHON_VERSION/Python-$PYTHON_VERSION.tgz && \
+    tar -zxf Python-$PYTHON_VERSION.tgz && \
+    cd Python-$PYTHON_VERSION && \
+    mkdir /opt/python/ && \
+    ./configure --prefix=/opt/python && \
+    make && \
+    make install && \
+    cd .. && \
+    rm Python-$PYTHON_VERSION.tgz && \
+    rm -r Python-$PYTHON_VERSION
+
+ENV PATH=/opt/python/bin:$PATH
+
+# Install OnnxTR
+ARG ONNXTR_REPO='felixdittrich92/onnxtr'
+ARG ONNXTR_VERSION=main
+RUN pip3 install -U pip setuptools wheel && \
+    pip3 install "onnxtr[$SYSTEM,html]@git+https://github.com/$ONNXTR_REPO.git@$ONNXTR_VERSION"

README.md

@@ -227,7 +227,7 @@ The smallest combination in OnnxTR (docTR) of `db_mobilenet_v3_large` and `crnn_
 |--------------------------------|-------------------------------|-------------------------------|
 |docTR (GPU) - v0.8.1            | ~0.07s / Page                 | ~0.05s / Page                 |
 |**docTR (GPU) float16** - v0.8.1| **~0.06s / Page**             | **~0.03s / Page**             |
-|OnnxTR (GPU) - v0.1.2           | coming soon                   | coming soon                   |
+|OnnxTR (GPU) - v0.1.2           | **~0.06s / Page**             | ~0.04s / Page                 |
 |EasyOCR (GPU) - v1.7.1          | ~0.31s / Page                 | ~0.19s / Page                 |
 |Surya (GPU) float16 - v0.4.4    | ~3.70s / Page                 | ~2.81s / Page                 |
 

onnxtr/models/engine.py

@@ -43,8 +43,8 @@ def run(self, inputs: np.ndarray) -> np.ndarray:
             inputs = np.broadcast_to(inputs, (self.fixed_batch_size, *inputs.shape))
             # combine the results
             logits = np.concatenate(
-                [self.runtime.run(self.output_name, {"input": batch})[0] for batch in inputs], axis=0
+                [self.runtime.run(self.output_name, {self.runtime_inputs.name: batch})[0] for batch in inputs], axis=0
             )
         else:
-            logits = self.runtime.run(self.output_name, {"input": inputs})[0]
+            logits = self.runtime.run(self.output_name, {self.runtime_inputs.name: inputs})[0]
         return shape_translate(logits, format="BHWC")