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--- |
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license: mit |
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base_model: |
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- Wan-AI/Wan2.2-I2V-A14B-Diffusers |
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- lightx2v/Wan2.2-Lightning |
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pipeline_tag: image-to-video |
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--- |
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This model is a merger of [Wan-AI/Wan2.2-I2V-A14B-Diffusers](https://huggingface.co/Wan-AI/Wan2.2-I2V-A14B-Diffusers) and [Wan2.2-Lightning v1 model](https://huggingface.co/lightx2v/Wan2.2-Lightning/tree/main/Wan2.2-I2V-A14B-4steps-lora-rank64-Seko-V1), it can be run with diffusers pipeline. |
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Running with [FastDM](https://github.com/KE-AI-ENG/FastDM): |
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``` |
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python gen.py --model-path FastDM/Wan2.2-I2V-A14B-Merge-Lightning-V1.0-Diffusers --architecture wan-i2v --guidance-scale 1.0 --height 480 --width 832 --steps 4 --use-fp8 --output-path ./output.mp4 --num-frames 81 --fps 16 --task i2v --prompts [PROMPTS] --image-path [PATH/TO/IMAGE] |
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``` |
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Running with diffusers: |
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```python |
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import torch |
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import numpy as np |
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from diffusers import WanImageToVideoPipeline |
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from diffusers.utils import export_to_video, load_image |
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model_id = "FastDM/Wan2.2-I2V-A14B-Merge-Lightning-V1.0-Diffusers" |
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dtype = torch.bfloat16 |
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device = "cuda" |
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pipe = WanImageToVideoPipeline.from_pretrained(model_id, torch_dtype=dtype) |
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pipe.to(device) |
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image = load_image( |
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"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG" |
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) |
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max_area = 480 * 832 |
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aspect_ratio = image.height / image.width |
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mod_value = pipe.vae_scale_factor_spatial * pipe.transformer.config.patch_size[1] |
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height = round(np.sqrt(max_area * aspect_ratio)) // mod_value * mod_value |
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width = round(np.sqrt(max_area / aspect_ratio)) // mod_value * mod_value |
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image = image.resize((width, height)) |
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prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside." |
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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" |
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generator = torch.Generator(device=device).manual_seed(0) |
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output = pipe( |
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image=image, |
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prompt=prompt, |
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negative_prompt=negative_prompt, |
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height=height, |
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width=width, |
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num_frames=81, |
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guidance_scale=1.0, |
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num_inference_steps=4, |
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generator=generator, |
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).frames[0] |
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export_to_video(output, "i2v_output.mp4", fps=16) |
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``` |
