SolitaryThinker
bbbb7ab021
Move all examples/inference and scripts off the legacy
VideoGenerator.from_pretrained(model, **kwargs) +
generate_video(prompt, **kwargs) surface onto the typed
from_config(GeneratorConfig(...)) + generate(GenerationRequest(...))
convention, including the Kandinsky-5 and DreamX-World examples added
on main after the original migration. git-mv api/compat.py to
api/translation.py ('compat' implied a temporary shim; the forward
translation is its honest permanent role) and repoint all importers,
tests, and doc links.
62 lines
2.7 KiB
Python
62 lines
2.7 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.api import (
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EngineConfig, GenerationRequest, GeneratorConfig, InputConfig, OffloadConfig, OutputConfig,
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)
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OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v"
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def main():
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# FastVideo will automatically use the optimal default arguments for the
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# model.
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# If a local path is provided, FastVideo will make a best effort
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# attempt to identify the optimal arguments.
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model_name = "Wan-AI/Wan2.2-TI2V-5B-Diffusers"
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generator = VideoGenerator.from_config(
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GeneratorConfig(
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model_path=model_name,
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engine=EngineConfig(
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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offload=OffloadConfig(
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dit=True,
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vae=False,
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text_encoder=True,
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pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
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# image_encoder=False,
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),
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),
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)
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)
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# I2V is triggered just by passing in an image_path argument
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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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image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
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video = generator.generate(
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GenerationRequest(
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prompt=prompt,
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inputs=InputConfig(image_path=image_path),
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output=OutputConfig(output_path=OUTPUT_PATH, save_video=True),
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)
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)
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# Generate another video with a different prompt, without reloading the
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# model!
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# T2V mode
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prompt2 = (
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"A majestic lion strides across the golden savanna, its powerful frame "
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"glistening under the warm afternoon sun. The tall grass ripples gently in "
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"the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
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"embodying the raw energy of the wild. Low angle, steady tracking shot, "
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"cinematic.")
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video2 = generator.generate(
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GenerationRequest(
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prompt=prompt2,
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output=OutputConfig(output_path=OUTPUT_PATH, save_video=True),
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)
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)
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if __name__ == "__main__":
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main()
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