feat: added simple Dockerfile to quickly run gradio app and instructions; fixed version in pip requirements.txt

Dockerfile

@@ -0,0 +1,27 @@
+FROM nvcr.io/nvidia/pytorch:23.05-py3
+
+ENV PYTHONDONTWRITEBYTECODE 1
+ENV PYTHONUNBUFFERED 1
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        make \
+        pkgconf \
+        xz-utils \
+        xorg-dev \
+        libgl1-mesa-dev \
+        libglu1-mesa-dev \
+        libxrandr-dev \
+        libxinerama-dev \
+        libxcursor-dev \
+        libxi-dev \
+        libxxf86vm-dev
+
+RUN pip install --upgrade pip
+
+COPY requirements.txt requirements.txt
+RUN pip install -r requirements.txt
+
+WORKDIR /workspace
+
+RUN (printf '#!/bin/bash\nexec \"$@\"\n' >> /entry.sh) && chmod a+x /entry.sh
+ENTRYPOINT ["/entry.sh"]

README.md

@@ -64,6 +64,19 @@ cat environment.yml | \
   grep -v -E 'nvidia|cuda' > environment-no-nvidia.yml && \
     conda env create -f environment-no-nvidia.yml
 conda activate stylegan3
+```
+
+## Run Gradio visualizer in Docker 
+
+Provided docker image is based on NGC PyTorch repository. To quickly try out visualizer in Docker, run the following:  
+
+```sh
+docker build . -t draggan:latest  
+docker run -v  "$PWD":/workspace/src -it draggan:latest bash  
+cd src && python visualizer_drag_gradio.py  
+```
+Now you can open a shared link from Gradio (printed in the terminal console).   
+Beware the Docker image takes about 25GB of disk space!
 
 # On MacOS
 export PYTORCH_ENABLE_MPS_FALLBACK=1

requirements.txt

@@ -1,9 +1,13 @@
-torch
+torch>=2.0.0
-torchvision
+scipy==1.11.0
-Ninja
+Ninja==1.10.2
-gradio
+gradio>=3.35.2
+imageio-ffmpeg>=0.4.3
 huggingface_hub
 hf_transfer
 pyopengl
 imgui
-glfw
+glfw==2.6.1
+pillow>=9.4.0
+torchvision>=0.15.2
+imageio>=2.9.0