| FROM python:3.10-slim | |
| ENV PYTHONDONTWRITEBYTECODE=1 \ | |
| PYTHONUNBUFFERED=1 \ | |
| PIP_NO_CACHE_DIR=1 \ | |
| PORT=7860 \ | |
| HOME=/home/user \ | |
| APP_ROOT=/app \ | |
| PATH=/home/user/.local/bin:$PATH \ | |
| HF_HOME=/tmp/.huggingface \ | |
| TRANSFORMERS_CACHE=/tmp/.cache/huggingface/transformers \ | |
| HUGGINGFACE_HUB_CACHE=/tmp/.cache/huggingface/hub\ | |
| PAPER_URL=https://ieeexplore.ieee.org/Xplore/home.jsp\ | |
| PAPER_TITLE='RG-DermNet: A Multimodal Attention-Based Model with Residual Block Usage for Skin Lesion Classification'\ | |
| PAPER_DESCRIPTION='Skin cancer accounts for nearly one-third of all diag-\nnosed tumors worldwide, making early and accurate recognition\ncritical for improving patient outcomes. In this work, we pro-\npose RG-DermNet, a multimodal deep learning framework that\nintegrates skin lesion images with structured clinical metadata\nthrough a residual gated-attention (RG-ATT) fusion mechanism.\nThe architecture combines CNN- and Transformer-based visual\nbackbones with a lightweight one-hot encoding pipeline for meta-\ndata, enabling effective cross-modal interaction. The proposed\nmodel is evaluated using a patient-wise cross-validation protocol\nacross four dermatological datasets with heterogeneous metadata.\nOn PAD-UFES-20, using Caformer-B36 as the visual backbone,\nRG-DermNet achieves an accuracy of 0.75 ± 0.05, balanced\naccuracy of 0.78 ± 0.03, F1-score of 0.77 ± 0.04, and AUC of\n0.95 ± 0.01, outperforming existing multimodal baselines under\nthe same evaluation setting. In addition, a SHAP-based analysis\nprovides insights into the contribution of clinical metadata to\nthe model’s predictions, supporting both performance gains and\ninterpretability.' | |
| RUN useradd -m -u 1000 user | |
| WORKDIR /app | |
| RUN apt-get update && apt-get install -y --no-install-recommends \ | |
| build-essential \ | |
| gcc \ | |
| g++ \ | |
| git \ | |
| libglib2.0-0 \ | |
| libsm6 \ | |
| libxext6 \ | |
| libxrender1 \ | |
| libgomp1 \ | |
| && rm -rf /var/lib/apt/lists/* | |
| RUN mkdir -p /tmp/.huggingface /tmp/.cache/huggingface/transformers /tmp/.cache/huggingface/hub | |
| COPY --chown=user requirements.txt $APP_ROOT/requirements.txt | |
| USER user | |
| RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \ | |
| pip install --no-cache-dir -r $APP_ROOT/requirements.txt | |
| COPY --chown=user . $APP_ROOT | |
| EXPOSE 7860 | |
| CMD ["python", "app.py"] | |