Davids048andClaude Opus 5.5
f571621ae7
Every example calls VideoGenerator.generate with a nested request instead of generate_video keywords, and passes settings outside the from_pretrained convenience keywords through VideoGenerator.from_config at their typed paths. Each request and generator config equals what the keyword call built. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
33 lines
943 B
Python
33 lines
943 B
Python
from fastvideo import VideoGenerator
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OUTPUT_PATH = "video_samples_kandinsky5_i2v"
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IMAGE_PATH = "assets/girl.png"
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def main():
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generator = VideoGenerator.from_pretrained(
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"kandinskylab/Kandinsky-5.0-I2V-Pro-distilled-5s-Diffusers",
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# "kandinskylab/Kandinsky-5.0-I2V-Pro-sft-5s-Diffusers"
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# "kandinskylab/Kandinsky-5.0-I2V-Lite-5s-Diffusers"
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num_gpus=1,
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use_fsdp_inference=False,
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dit_cpu_offload=False,
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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pin_cpu_memory=True,
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# image_encoder_cpu_offload=False,
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)
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prompt = ("A woman stands up and walks away")
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_ = generator.generate({
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"prompt": prompt,
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"inputs": {"image_path": IMAGE_PATH},
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"sampling": {"height": 1024, "width": 1024, "num_frames": 121},
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"output": {"output_path": OUTPUT_PATH, "save_video": True},
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})
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if __name__ == "__main__":
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main()
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