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+# Use a stable Python 3.10 base image (buster-slim) for better compatibility with Pillow build.
+# This is a CPU-only base image.
+FROM python:3.10-slim-buster
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Install system dependencies
+# These are commonly needed for Python packages like Pillow (for image processing)
+# and for general development utilities.
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    libgl1-mesa-glx \
+    libgomp1 \
+    git \
+    git-lfs \
+    ffmpeg \
+    libsm6 \
+    libxext6 \
+    cmake \
+    rsync \
+    && rm -rf /var/lib/apt/lists/* \
+    && git lfs install
+
+# --- OPTIONAL: CUDA/GPU Installation (uncomment ONLY if you need GPU and select GPU hardware) ---
+# If you enable these lines, make sure your Hugging Face Space has GPU hardware selected.
+# Otherwise, keep them commented out for CPU-only deployment.
+# These steps are for installing CUDA toolkit and PyTorch with CUDA support on a slim-buster image.
+# You would replace the PyTorch and CUDA versions with what you need.
+# ENV CUDA_VERSION=11.8
+# ENV CUDNN_VERSION=8
+# ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
+# ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:${LD_LIBRARY_PATH}
+# RUN apt-get update && apt-get install -y --no-install-recommends \
+#     cuda-keyring-11-8 \
+#     cuda-toolkit-11-8 \
+#     libcudnn8=${CUDNN_VERSION}.*-1+cuda${CUDA_VERSION} \
+#     libcudnn8-dev=${CUDNN_VERSION}.*-1+cuda${CUDA_VERSION} \
+#     && rm -rf /var/lib/apt/lists/*
+# RUN pip install --no-cache-dir torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118
+# ENV USE_GPU=true
+# --- END OPTIONAL CUDA/GPU Installation ---
+
+# Copy the requirements file into the container
+COPY requirements.txt .
+
+# Install Python dependencies from requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the application code into the container
+COPY app.py .
+
+# Expose the port Flask runs on
+EXPOSE 5000
+
+# Set an environment variable for GPU usage.
+# If you uncommented the CUDA installation above, USE_GPU should be true.
+# Otherwise, for CPU-only, keep it false.
+ENV USE_GPU=false # Set to 'true' if you uncommented the CUDA/PyTorch installation above
+
+# Command to run the Flask application using gunicorn for production serving.
+CMD ["gunicorn", "--bind", "0.0.0.0:5000", "app:app"]