Create Dockerfile

Dockerfile

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+# Use an official PyTorch image with CUDA support as the base image
+FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
+
+# Install Git
+RUN apt-get update && apt-get install -y git
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+
+# Switch to the "user" user
+USER user
+
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH \
+    PYTHONPATH=$HOME/app \
+	PYTHONUNBUFFERED=1 \
+	GRADIO_ALLOW_FLAGGING=never \
+	GRADIO_NUM_PORTS=1 \
+	GRADIO_SERVER_NAME=0.0.0.0 \
+	GRADIO_THEME=huggingface \
+    GRADIO_SHARE=False \
+	SYSTEM=spaces
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Clone your repository or add your code to the container
+RUN git clone -b main https://github.com/Algolzw/daclip-uir $HOME/app
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the pretrained file and folder into the working directory
+COPY pretrained/ $HOME/app/universal-image-restoration/config/daclip-sde/options/
+
+# Set the working directory to the app.py file's location
+WORKDIR $HOME/app/universal-image-restoration/config/daclip-sde/
+
+# Set the environment variable to specify the GPU device
+ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
+ENV CUDA_VISIBLE_DEVICES=0
+
+# Run your app.py script
+CMD ["python", "app.py"]