Adding docker support

.dockerignore

@@ -0,0 +1,46 @@
+# Git files
+.git
+.gitignore
+
+# Python
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
+env
+.venv
+venv
+.env
+
+# IDE
+.vscode
+.idea
+*.swp
+*.swo
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Build artifacts
+build/
+dist/
+*.egg-info
+
+# Work directories (will be mounted)
+work_dir/*
+show_dir/*
+
+# Logs
+*.log
+logs/
+
+# Documentation
+docs/
+*.md
+!README.md
+
+# Cache
+.cache/
+.pytest_cache/

Dockerfile

@@ -0,0 +1,107 @@
+FROM pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel
+
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+ENV CUDA_HOME=/usr/local/cuda
+ENV PATH=${CUDA_HOME}/bin:${PATH}
+ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    wget \
+    curl \
+    vim \
+    unzip \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    gcc \
+    g++ \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /workspace
+
+# Install Python dependencies
+RUN pip install --upgrade pip
+
+# Install OpenMMLab suite with pre-compiled CUDA extensions
+RUN pip install -U openmim
+RUN mim install mmengine
+RUN mim install "mmcv>=2.0.0rc4,<2.2.0" -f https://download.openmmlab.com/mmcv/dist/cu117/torch2.0.0/index.html
+RUN mim install "mmdet>=3.0.0,<4.0.0"
+RUN mim install "mmpretrain>=1.0.0"
+
+# Install additional dependencies for UltraSam
+RUN pip install \
+    tensorboard \
+    matplotlib \
+    seaborn \
+    scipy \
+    scikit-image \
+    Pillow \
+    opencv-python \
+    tqdm \
+    yapf
+
+# Force install compatible NumPy version AFTER other dependencies to avoid conflicts
+RUN pip install "numpy==1.26.4" --force-reinstall --no-deps
+
+# Verify MMCV CUDA extensions are working
+RUN python -c "import torch; print('PyTorch:', torch.__version__); print('CUDA available:', torch.cuda.is_available())"
+RUN python -c "import mmcv; print('MMCV:', mmcv.__version__)"
+RUN python -c "from mmcv.ops import roi_align; print('MMCV CUDA extensions: OK')"
+RUN python -c "import mmdet; print('MMDetection:', mmdet.__version__)"
+RUN python -c "import mmpretrain; print('MMPretrain:', mmpretrain.__version__)"
+
+# Copy UltraSam code
+COPY . /workspace/UltraSam/
+WORKDIR /workspace/UltraSam
+
+# Set Python path
+ENV PYTHONPATH=/workspace/UltraSam:/workspace/UltraSam/endosam
+
+# Create necessary directories
+RUN mkdir -p work_dir show_dir
+
+# Copy UltraSam weights from host directory, or download if not present
+RUN echo "=== UltraSam weights setup ===" && \
+    if [ -f "UltraSam.pth" ]; then \
+        echo "Using existing UltraSam.pth from host directory" && \
+        ls -lh UltraSam.pth; \
+    else \
+        echo "UltraSam.pth not found, downloading..." && \
+        wget --progress=bar:force -O UltraSam.pth "https://s3.unistra.fr/camma_public/github/ultrasam/UltraSam.pth" && \
+        echo "Download complete. File size: $(ls -lh UltraSam.pth)"; \
+    fi && \
+    echo "Verifying UltraSam weights..." && \
+    file UltraSam.pth && \
+    echo "Backing up weights for volume mount scenarios..." && \
+    cp UltraSam.pth /tmp/UltraSam.pth
+
+# Final verification
+RUN echo "=== Build verification ===" && \
+    ls -la UltraSam.pth && \
+    echo "UltraSam.pth size: $(stat -f%z UltraSam.pth 2>/dev/null || stat -c%s UltraSam.pth) bytes" && \
+    echo "=== Environment ready ==="
+
+# Create entrypoint script to handle volume mount scenarios
+RUN echo '#!/bin/bash\n\
+echo "=== Container startup ==="\n\
+if [ ! -f "/workspace/UltraSam/UltraSam.pth" ]; then\n\
+    echo "UltraSam.pth not found in working directory, copying from backup..."\n\
+    cp /tmp/UltraSam.pth /workspace/UltraSam/UltraSam.pth\n\
+    echo "UltraSam.pth restored: $(ls -lh /workspace/UltraSam/UltraSam.pth)"\n\
+else\n\
+    echo "UltraSam.pth found: $(ls -lh /workspace/UltraSam/UltraSam.pth)"\n\
+fi\n\
+echo "=== Ready for execution ==="\n\
+exec "$@"' > /entrypoint.sh && chmod +x /entrypoint.sh
+
+# Set entrypoint and default command
+ENTRYPOINT ["/entrypoint.sh"]
+
+CMD ["/bin/bash"]

README.md

@@ -11,7 +11,7 @@ _Adrien Meyer, Aditya Murali, Farahdiba Zarin, Didier Mutter, Nicolas Padoy_
 ## Minimal working example
 <details>
 <summary>Click to expand Install</summary>
-This example guide you to download and use UltraSam in inference mode in a sample dataset.
+This example guides you to download and use UltraSam in inference mode in a sample dataset.
 The sample dataset, coco-based, is in "./sample_dataset" (using MMOTU2D samples).
 
 Clone the repo
@@ -51,6 +51,64 @@ It will run inference on the specified sample dataset, modified inline from the
 
 </details>
 
+## Docker Alternative
+
+<details>
+<summary>Click to expand Docker setup</summary>
+
+Docker provides the simplest way to run UltraSam with all dependencies pre-configured.
+
+### Prerequisites
+- Docker Engine with GPU support
+- NVIDIA Container Toolkit for GPU access
+- NVIDIA drivers compatible with CUDA 11.7
+
+### Quick Docker Setup
+
+1. **Clone and build:**
+```bash
+git clone https://github.com/CAMMA-public/UltraSam
+cd UltraSam
+docker build -t ultrasam:latest .
+```
+
+2. **Run sample inference:**
+
+To lauch the docker
+
+```bash
+docker run --rm --gpus all -it -v $(pwd):/workspace/UltraSam ultrasam:latest bash
+```
+
+Run a sample test script inside the container:
+
+```bash
+python visual_inference.py
+```
+
+To run a sample inference test using MMDet directly from host:
+
+```bash
+docker run --rm --gpus all -v $(pwd):/workspace/UltraSam \
+    ultrasam:latest bash -c "
+    cd /workspace/UltraSam && \
+    mim test mmdet configs/UltraSAM/UltraSAM_full/UltraSAM_box_refine.py \
+        --checkpoint UltraSam.pth \
+        --cfg-options test_dataloader.dataset.data_root='sample_dataset' \
+                     test_dataloader.dataset.ann_file='sample_coco_MMOTU2D.json' \
+                     test_dataloader.dataset.data_prefix.img='sample_images' \
+                     test_evaluator.ann_file='sample_dataset/sample_coco_MMOTU2D.json' \
+        --work-dir ./work_dir/example \
+        --show-dir ./show_dir"
+```
+
+**Docker Features:**
+- PyTorch 2.0.0 with CUDA 11.7 support
+- Pre-compiled MMCV, MMDetection, and MMPretrain
+- All dependencies with compatible versions (NumPy 1.26.4 enforced for tensor compatibility)
+- Ready-to-use environment with PYTHONPATH configured
+
+</details>
 
 ## Usage
 
@@ -82,7 +140,7 @@ pip install scipy
 
 Pre-trained UltraSam model checkpoint is accessible [at this link](https://s3.unistra.fr/camma_public/github/ultrasam/UltraSam.pth).
 
-To train / test, you will need a coco.json annotation file, and create a symbolik link to it, or modify the config files to point to your annotation file.
+To train / test, you will need a coco.json annotation file, and create a symbolic link to it, or modify the config files to point to your annotation file.
 
 To train from scratch, you can use the code in ```weights``` to download and convert SAM, MEDSAM and adapters weights.
 

docker-compose.yml

@@ -0,0 +1,23 @@
+version: '3.8'
+
+services:
+  ultrasam:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    container_name: ultrasam-gpu
+    runtime: nvidia
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=all
+      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
+      - CUDA_VISIBLE_DEVICES=0,1  # Adjust based on your GPU setup
+    volumes:
+      - .:/workspace/UltraSam
+      - ./work_dir:/workspace/UltraSam/work_dir
+      - ./show_dir:/workspace/UltraSam/show_dir
+      - ./sample_dataset:/workspace/UltraSam/sample_dataset
+    working_dir: /workspace/UltraSam
+    stdin_open: true
+    tty: true
+    shm_size: 8gb  # Increase shared memory for multi-processing
+    command: /bin/bash