--- title: Real-Time Latent Consistency Model Image-to-Image ControlNet emoji: 🖼️🖼️ colorFrom: gray colorTo: indigo sdk: docker pinned: false suggested_hardware: a10g-small --- # Real-Time Latent Consistency Model 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. You need a webcam to run this demo. 🤗 See a collecting with live demos [here](https://huggingface.co./collections/latent-consistency/latent-consistency-model-demos-654e90c52adb0688a0acbe6f) ## Running Locally You need CUDA and Python 3.10, Mac with an M1/M2/M3 chip or Intel Arc GPU `TIMEOUT`: limit user session timeout `SAFETY_CHECKER`: disabled if you want NSFW filter off `MAX_QUEUE_SIZE`: limit number of users on current app instance `TORCH_COMPILE`: enable if you want to use torch compile for faster inference works well on A100 GPUs ## Install ```bash python -m venv venv source venv/bin/activate pip3 install -r requirements.txt ``` # LCM ### Image to Image ```bash uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload ``` ### Image to Image ControlNet Canny Based pipeline from [taabata](https://github.com/taabata/LCM_Inpaint_Outpaint_Comfy) ```bash uvicorn "app-controlnet:app" --host 0.0.0.0 --port 7860 --reload ``` ### Text to Image ```bash uvicorn "app-txt2img:app" --host 0.0.0.0 --port 7860 --reload ``` # LCM + LoRa 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) ### Image to Image ControlNet Canny LoRa ```bash uvicorn "app-controlnetlora:app" --host 0.0.0.0 --port 7860 --reload ``` ### Text to Image ```bash uvicorn "app-txt2imglora:app" --host 0.0.0.0 --port 7860 --reload ``` ### Setting environment variables ```bash TIMEOUT=120 SAFETY_CHECKER=True MAX_QUEUE_SIZE=4 uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload ``` If you're running locally and want to test it on Mobile Safari, the webserver needs to be served over HTTPS. ```bash openssl req -newkey rsa:4096 -nodes -keyout key.pem -x509 -days 365 -out certificate.pem uvicorn "app-img2img:app" --host 0.0.0.0 --port 7860 --reload --log-level info --ssl-certfile=certificate.pem --ssl-keyfile=key.pem ``` ## Docker You need NVIDIA Container Toolkit for Docker ```bash docker build -t lcm-live . docker run -ti -p 7860:7860 --gpus all lcm-live ``` or with environment variables ```bash docker run -ti -e TIMEOUT=0 -e SAFETY_CHECKER=False -p 7860:7860 --gpus all lcm-live ``` # Demo on Hugging Face https://huggingface.co./spaces/radames/Real-Time-Latent-Consistency-Model https://github.com/radames/Real-Time-Latent-Consistency-Model/assets/102277/c4003ac5-e7ff-44c0-97d3-464bb659de70