huggingface / huggingface/diffusers

Wan-AI/Wan2.2-TI2V-5B-Diffusers Image to Video Missing

Aperta
#13,258 1 commento 0 reazioni 0 assegnatari Vedi su GitHub
bug
Lingua principale
Python
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34.5k
Fork
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Merge medio
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PR unite (30g)
91

Descrizione

### Describe the bug

I cannot make it that the 5B version takes in an image and generate a video out of it

```
import torch
import numpy as np
from diffusers import WanPipeline, AutoencoderKLWan, WanTransformer3DModel, UniPCMultistepScheduler
from diffusers.utils import export_to_video, load_image

dtype = torch.bfloat16
device = "cuda"

model_id = "Wan-AI/Wan2.2-TI2V-5B-Diffusers"
vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=dtype)
pipe.to(device)

height = 704
width = 1280
num_frames = 121
num_inference_steps = 50
guidance_scale = 5.0

prompt = "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage."
negative_prompt = "色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走"

output = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
height=height,
width=width,
num_frames=num_frames,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
).frames[0]
export_to_video(output, "5bit2v_output.mp4", fps=24)

```

It says image is not part of the pipeline

### Reproduction

latest

### Logs

```shell

```

### System Info

latest

### Who can help?

_No response_

Guida per i contributori

Apri la guida per i contributori

Direzione di ricerca

Start by running the provided WanPipeline example with the Wan-AI/Wan2.2-TI2V-5B-Diffusers model and inspect the WanPipeline entry point and its documented inputs. Done means the 5B pipeline accepts an image alongside the prompt and produces the expected exported video, with coverage for the image-to-video path.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
python, pytorch
Ambito
computer-vision, machine-learning
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Ferma
Chiarezza
Da chiarire
Idoneità per principianti
30/100

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