Update Dockerfile

Dockerfile

@@ -1,35 +1,34 @@
-# Start from a stable, slim Python base image
-FROM python:3.13-slim
+# Use a lightweight Python base image
+FROM python:3.9-slim
 
-# Set the working directory inside the container
-WORKDIR /app
+# Set working directory
+WORKDIR /code
 
-# Switch to root user to install system packages
-USER root
+# Install system dependencies required for OpenCV
+# libgl1-mesa-glx and libglib2.0-0 are critical for cv2 to work in Docker
+RUN apt-get update && apt-get install -y \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
 
-# === THIS IS THE FIX ===
-# Update the package list and install 'build-essential'
-# build-essential includes gcc and other necessary C/C++ compilers
-RUN apt-get update && \
-    apt-get install -y build-essential && \
-    rm -rf /var/lib/apt/lists/*
-# === END OF FIX ===
-
-# Copy the requirements file first for layer caching
+# Copy requirements file first to leverage Docker caching
 COPY requirements.txt .
 
 # Install Python dependencies
-# --no-cache-dir reduces image size
-# --prefer-binary to speed up install if possible
-RUN pip install --no-cache-dir --prefer-binary -r requirements.txt
+# We use the CPU version of PyTorch to keep the image size small for deployment
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
-# Copy the rest of the application code
-# This includes app.py and classifier.pkl (which you must upload)
+# Copy the application code and the model
 COPY . .
 
-# Hugging Face Spaces requires the app to listen on port 7860
+# Create a non-root user (Hugging Face security requirement)
+RUN useradd -m -u 1000 user
+USER user
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# Expose the port Hugging Face expects
 EXPOSE 7860
 
-# Command to run the FastAPI server using uvicorn
-# --host 0.0.0.0 makes it accessible from outside the container
+# Command to run the application
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]