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Dockerfile.nvidia

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+FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
+
+# Always use UTC on a server
+RUN ln -snf /usr/share/zoneinfo/UTC /etc/localtime && echo UTC > /etc/timezone
+
+RUN DEBIAN_FRONTEND=noninteractive apt update && apt install -y python3 python3-pip python3-tk git ffmpeg nvidia-cuda-toolkit nvidia-container-runtime libnvidia-decode-525-server wget unzip
+RUN wget https://github.com/deepinsight/insightface/releases/download/v0.7/buffalo_l.zip -O /tmp/buffalo_l.zip && \
+        mkdir -p /root/.insightface/models/buffalo_l && \
+        cd /root/.insightface/models/buffalo_l && \
+        unzip /tmp/buffalo_l.zip && \
+        rm -f /tmp/buffalo_l.zip
+
+RUN pip install nvidia-tensorrt
+RUN git clone https://github.com/xaviviro/refacer && cd refacer && pip install -r requirements-GPU.txt
+
+WORKDIR /refacer
+
+# Test following commands in container to make sure GPU stuff works
+# nvidia-smi
+# python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

run.sh

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+#!/bin/bash
+# Run this script from within the refacer/docker folder.
+# You'll need inswrapper_128.onnx from either:
+#    https://drive.google.com/file/d/1eu60OrRtn4WhKrzM4mQv4F3rIuyUXqfl/view?usp=drive_link
+# or https://drive.google.com/file/d/1jbDUGrADco9A1MutWjO6d_1dwizh9w9P/view?usp=sharing
+# or https://mega.nz/file/9l8mGDJA#FnPxHwpdhDovDo6OvbQjhHd2nDAk8_iVEgo3mpHLG6U
+# or https://1drv.ms/u/s!AsHA3Xbnj6uAgxhb_tmQ7egHACOR?e=CPoThO
+# or https://civitai.com/models/80324?modelVersionId=85159
+
+docker stop -t 0 refacer
+docker build -t refacer -f Dockerfile.nvidia . && \
+    docker run --rm --name refacer -v $(pwd)/..:/refacer -p 7860:7860 --gpus all refacer python3 app.py --server_name 0.0.0.0 &
+sleep 2 && google-chrome --new-window "http://127.0.0.1:7860" &