yolo算法 - 目标识别算法

# yolo-diffusion [](https://colab.research.google.com/github/jermwatt/yolo_diffusion/blob/main/object_diffusion_demo.ipynb) A simple demo for quick experimentation with [Stable Diffusion 2.0](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting) applied to specific objects in 2d images, detected and segmented via [YOLOv8](https://docs.ultralytics.com/). You can get started in [collab now](https://colab.research.google.com/github/jermwatt/yolo_diffusion/blob/main/object_diffusion_demo.ipynb) - or watch the walkthrough videos below first. ## Overview With this simple demo you can start with any image - like the one on the left below. You can then select any object in the image - like the `pizza`. YOLO will detect and segment this object, and then you can replace it with a diffused suggestion via Stable v2.0.  Like "a pile of cash" - shown on the right. You can take the same image and do the same thing with another object - like the `cat` - as shown below.  Here we used the prompt "'sinister looking cartoon squirrel wearing sunglasses, high resolution'". Here's another example. In this case we replace the `person` with 'an ape, smiling, high resolution, holding something"  YOLOv8 has more than 70 pre-trained objects that can be quickly detected / segmented, then fed to Stable Diffusion. See the [demo notebook](https://colab.research.google.com/github/jermwatt/yolo-diffusion/blob/main/object_diffusion_demo.ipynb#scrollTo=8GhUUsG2tdZ1) for a complete list of available objects.