ADD Dockerfile

Dockerfile

@@ -0,0 +1,80 @@
+# Use an official PyTorch image with CUDA support as the base image
+FROM pytorch/pytorch:2.0.0-cuda11.7-cudnn8-devel
+
+# Add NVIDIA CUDA GPG key
+# Add NVIDIA CUDA GPG key using a different key server
+RUN apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-key A4B469963BF863CC
+
+# Install Git and system libraries required for OpenGL without interactive prompts
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install Git, OpenGL libraries, and libglib2.0
+RUN apt-get update && apt-get install -y git libgl1-mesa-glx libglib2.0-0
+
+RUN apt-get update && apt-get install -y ninja-build
+
+# Install necessary dependencies, including CMake, a C++ compiler, and others
+RUN apt-get update && apt-get install -y unzip ffmpeg cmake g++ build-essential aria2
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+
+# Switch to the "user" user
+USER user
+
+# Set environment variables
+ENV HOME=/home/user \
+    CUDA_HOME=/usr/local/cuda \
+    PATH=/home/user/.local/bin:$PATH \
+    LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH} \
+    LIBRARY_PATH=${CUDA_HOME}/lib64/stubs:${LIBRARY_PATH} \
+    PYTHONPATH=$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/fffiloni/video-retalking $HOME/app
+
+# Install specific versions of PyTorch and TorchVision
+RUN pip install torch==2.0.0+cu117 torchvision==0.15.0+cu117 -f https://download.pytorch.org/whl/torch_stable.html
+
+# Install dependencies
+#COPY requirements.txt $HOME/app/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt gradio moviepy
+
+# Download checkpoint files using aria2
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/30_net_gen.pth -d $HOME/app/checkpoints -o 30_net_gen.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/BFM.zip -d $HOME/app/checkpoints -o BFM.zip
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/DNet.pt -d $HOME/app/checkpoints -o DNet.pt
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/ENet.pth -d $HOME/app/checkpoints -o ENet.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/GFPGANv1.3.pth -d $HOME/app/checkpoints -o GFPGANv1.3.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/GPEN-BFR-512.pth -d $HOME/app/checkpoints -o GPEN-BFR-512.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/LNet.pth -d $HOME/app/checkpoints -o LNet.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/ParseNet-latest.pth -d $HOME/app/checkpoints -o ParseNet-latest.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/RetinaFace-R50.pth -d $HOME/app/checkpoints -o RetinaFace-R50.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/expression.mat -d $HOME/app/checkpoints -o expression.mat
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/face3d_pretrain_epoch_20.pth -d $HOME/app/checkpoints -o face3d_pretrain_epoch_20.pth
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/shape_predictor_68_face_landmarks.dat -d $HOME/app/checkpoints -o shape_predictor_68_face_landmarks.dat
+RUN unzip -d $HOME/app/checkpoints/BFM $HOME/app/checkpoints/BFM.zip
+
+# Ensure the compiled CUDA code can be found
+ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+
+# Update package lists and install other dependencies as needed
+# Ensure that CUDA components are correctly installed and configured
+# Install any other required packages
+
+# 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"]

README.md

@@ -1,12 +1,11 @@
 ---
-title: LipSync
+title: LipSync from Algmon
 emoji: 🌍
 colorFrom: gray
 colorTo: purple
-sdk: gradio
-sdk_version: 4.12.0
-app_file: app.py
-pinned: false
+sdk: docker
+pinned: true
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+arxiv.org/abs/2211.14758

app.py

@@ -1,7 +0,0 @@
-import gradio as gr
-
-def greet(name):
-    return "Hello " + name + "!!"
-
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()