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--- |
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title: Real-Time Latent Consistency Model Image-to-Image ControlNet |
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emoji: 🖼️🖼️ |
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colorFrom: gray |
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colorTo: indigo |
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sdk: docker |
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pinned: false |
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suggested_hardware: a10g-small |
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--- |
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# Real-Time Latent Consistency Model |
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This demo showcases [Latent Consistency Model (LCM)](https://huggingface.co./SimianLuo/LCM_Dreamshaper_v7) using [Diffusers](https://github.com/huggingface/diffusers/tree/main/examples/community#latent-consistency-pipeline) with a MJPEG stream server. |
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You need a webcam to run this demo. 🤗 |
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## Running Locally |
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You need CUDA and Python 3.10, Mac with an M1/M2/M3 chip or Intel Arc GPU |
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`TIMEOUT`: limit user session timeout |
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`SAFETY_CHECKER`: disabled if you want NSFW filter off |
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`MAX_QUEUE_SIZE`: limit number of users on current app instance |
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`TORCH_COMPILE`: enable if you want to use torch compile for faster inference works well on A100 GPUs |
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## Install |
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```bash |
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python -m venv venv |
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source venv/bin/activate |
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pip3 install -r requirements.txt |
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``` |
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# LCM |
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### Image to Image |
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```bash |
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uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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### Image to Image ControlNet Canny |
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Based pipeline from [taabata](https://github.com/taabata/LCM_Inpaint_Outpaint_Comfy) |
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```bash |
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uvicorn "app-controlnet:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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### Text to Image |
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```bash |
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uvicorn "app-txt2img:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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# LCM + LoRa |
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Using LCM-LoRA, giving it the super power of doing inference in as little as 4 steps. [Learn more here](https://huggingface.co./blog/lcm_lora) or [technical report](https://huggingface.co./papers/2311.05556) |
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### Image to Image ControlNet Canny LoRa |
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```bash |
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uvicorn "app-controlnetlora:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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### Text to Image |
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```bash |
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uvicorn "app-txt2imglora:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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### Setting environment variables |
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```bash |
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TIMEOUT=120 SAFETY_CHECKER=True MAX_QUEUE_SIZE=4 uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload |
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``` |
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If you're running locally and want to test it on Mobile Safari, the webserver needs to be served over HTTPS. |
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```bash |
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openssl req -newkey rsa:4096 -nodes -keyout key.pem -x509 -days 365 -out certificate.pem |
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uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload --log-level info --ssl-certfile=certificate.pem --ssl-keyfile=key.pem |
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``` |
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## Docker |
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You need NVIDIA Container Toolkit for Docker |
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```bash |
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docker build -t lcm-live . |
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docker run -ti -p 7860:7860 --gpus all lcm-live |
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``` |
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or with environment variables |
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```bash |
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docker run -ti -e TIMEOUT=0 -e SAFETY_CHECKER=False -p 7860:7860 --gpus all lcm-live |
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``` |
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# Demo on Hugging Face |
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https://huggingface.co./spaces/radames/Real-Time-Latent-Consistency-Model |
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https://github.com/radames/Real-Time-Latent-Consistency-Model/assets/102277/c4003ac5-e7ff-44c0-97d3-464bb659de70 |
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