Test script fromdiffusersimportStableDiffusionLatentUpscalePipeline,StableDiffusionPipelineimporttorchpipeline=StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5",torch_dtype=torch.float16)pipeline.to("cuda")upscaler=StableDiffusionLatentUpscalePipeline.from_pretrained("stabilityai/sd-x2-late...
Sampling Steps（采样步数）Stable Diffusion 的⼯作⽅式是从以随机⾼斯噪声起步，向符合提⽰的图...
熟悉ComfyUI后可对Stable Diffusion的工作流程更加熟悉，也可以组合出更多用法，或许以前在A1111的WebUI中...
This procedure can, for example, also be used to upscale samples from the base model. Comments Our codebase for the diffusion models builds heavily onOpenAI's ADM codebaseandhttps://github.com/lucidrains/denoising-diffusion-pytorch. Thanks for open-sourcing!
Stable Diffusionの優れた拡張機能が使えるアプリとして有名なAUTOMATIC1111さんのstable-diffusion-webuiがありますが、中でも高画質化に貢献するHires.fixをDiffusersだけで再現できないかと思い、実装してみました。 実装のリポジトリ こちらにアップロードしました。あくまで私が解釈した処理なの...
A latent text-to-image diffusion model. Contribute to CompVis/stable-diffusion development by creating an account on GitHub.
Stable Video Diffusion samples. Top: Text-to-Video generation. Middle: (Text-to-)Image-to-Video generation. Bottom: Multi- view synthesis via Image-to-Video finetuning. Abstract We present Stable Video Diffusion — a latent video diffu- sion model for high-resolution, sta...
所有图像基于 cmdr2 的 stable-diffusion-ui 的IMG2IMG 管线采样: { "default_seed": 232408816, "face_correction": null, "guidance_scale": 7.5, "height": 512, "inference_steps": 80, "init_image": "94fc1260", "mask_image": "00000000", "prompt_strength": 0.75, "prompts": [ "matting...
bucket_no_upscale: False[Subset 0 of Dataset 0]image_dir: "D:\ruanjian\lora\lora-scripts-v1.5.1\train\liliai\10_liliai"image_count: 21num_repeats: 10shuffle_caption: Truekeep_tokens: 0caption_dropout_rate: 0.0caption_dropout_every_n_epoches: 0caption_tag_dropout_rate: 0.0caption_prefix...
bucket_no_upscale: False[Subset 0 of Dataset 0]image_dir: "D:\ruanjian\lora\lora-scripts-v1.5.1\train\liliai\10_liliai"image_count: 21num_repeats: 10shuffle_caption: Truekeep_tokens: 0caption_dropout_rate: 0.0caption_dropout_every_n_epoches: 0caption_tag_dropout_rate: 0.0caption_prefix...