HomeSenseTest / Dockerfile
YusufMesbah's picture
Implement initial version of SegFormer training pipeline with dataset parsing and model training functionalities. Added Dockerfile for environment setup, utility scripts for parsing and training, and Gradio interface for user interaction.
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FROM pytorch/pytorch:2.8.0-cuda12.9-cudnn9-runtime
ENV PYTHONUNBUFFERED=1
RUN useradd -m -u 1000 user
WORKDIR /app
# Install system dependencies for building Python packages
RUN apt-get update && apt-get install -y \
build-essential \
libffi-dev \
libssl-dev \
ffmpeg \
libsm6 \
libxext6 \
libmagic1 \
&& rm -rf /var/lib/apt/lists/*
# Create virtual environment for Sly (keep isolated)
RUN python -m venv /app/.venv-sly
RUN /app/.venv-sly/bin/pip install --upgrade pip
COPY --chown=user requirements-sly.txt requirements-sly.txt
RUN /app/.venv-sly/bin/pip install -r requirements-sly.txt
# Install Gradio and other dependencies
RUN pip install --upgrade pip
COPY --chown=user requirements.txt requirements.txt
RUN pip install -r requirements.txt
# Copy the rest of the app
COPY --chown=user . .
ENV GRADIO_SERVER_NAME="0.0.0.0"
CMD ["python", "app.py"]