官方目前放出了 2 款模型,分别是 SVD 和 SVD-XT(文末有模型资源包),其中 SVD 可以生成 14 帧的视频,SVD-XT 可以生成 25 帧的视频。 它们还分别有一个升级版本 svd_image_decoder 和 svd_xt_image_decoder,是将 sd1.5/sd2.1 vae 添加到了原本的模型中,可以让生成的视频细节更好,但是总体的稳定性不太...
在Load Image节点中导入图片后,右键选择Open in MaskEditor即可涂抹重绘部分。 2.效果展示 Stable Video Diffusion(只能通过ComfyUI进行使用) 一.核心参数 1.SVD模型下载,模型通过此节点调用,svd.safetensors可在 576×1024 分辨率下生成 14 帧运动片段,svd_image_decoder.safetensors可在相同分辨率下生成 25 帧运动...
它们还分别有一个升级版本 svd_image_decoder 和 svd_xt_image_decoder,是将 sd1.5/sd2.1 vae 添加到了原本的模型中,可以让生成的视频细节更好,但是总体的稳定性不太好。 SVD 模型地址: https://huggingface.co/stabilityai/stable-video-diffusion-img2vid/tree/main SVD-XT 模型地址: https://huggingface....
它们还分别有一个升级版本svd_image_decoder和svd_xt_image_decoder,是将sd1.5/sd2.1vae添加到了原本的模型中,官方说是用来让生成的视频细节更好,我个人是很少使用的。 svd_xt_1_1是在svd Image-to-Video [25 frames]模型的微调,文件大小少了一半,并实现了更高的输出一致性,更有性价比。同时清晰度以及自然...
程序请求的模型文件有4个: svd.safetensors svd_xt.safetensors svd_xt_image_decoder.safetensors svd_image_decoder.safetensors 其实svd后来还有一个模型 svd_xt_1_1.safetensors 都一并放在新目录下即可。 重新启动ComfyUI时不再提示下载svd模型。
https:///stabilityai/stable-video-diffusion-img2vid-xt/blob/main/svd_xt_image_decoder.safetensors 1. 2. 3. 4. 网盘地址: https://pan.baidu.com/s/1vdBDgPl254FOxZP2LBsHGg?pwd=iyme 放在checkpoints/目录下: 三、创建环境 创建一个独立的环境,比如叫img2video: ...
At the decoder side, the header of each compressed tile is read and the information is sent to the HC-RIOT decoder or to the inverse quantization, in order to recover the tile. The proposed system is applied to image coding and its performance is discussedHumberto Ochoa...
bec00900734f25e0c52638c1aa75b4e7 checkpoints/svd_xt_image_decoder.safetensors The error seems to be related to the fact that streamlet is trying to run the model before you uploaded the image. If you just ignore this error and upload an image, everything will work. ...
self.image_encoder: SVDImageEncoder = None self.unet: SVDUNet = None self.vae_encoder: SVDVAEEncoder = None self.vae_decoder: SVDVAEDecoder = None def fetch_main_models(self, model_manager: ModelManager): self.image_encoder = model_manager.image_encoder self.unet = model_manager.unet self...
The results in their work showed that by applying orthogonal regularization, the generator allows fine-tuning the tradeoff between fidelity and diversity of samples by truncating hidden spaces, which can make the model achieve the best performance in the image synthesis of class conditions. Another ...