Files
hao-ai-lab-FastVideo/examples/inference/basic/basic_wan2_2_i2v.py
T
Davids048andClaude Opus 5.5 f571621ae7 [refactor]: move examples to generate(request) and from_config
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
2026-10-03 02:14:36 +00:00

48 lines
1.9 KiB
Python

from fastvideo import VideoGenerator
# from fastvideo.api.sampling_param import SamplingParam
OUTPUT_PATH = "video_samples_wan2_2_14B_i2v"
def main():
# FastVideo will automatically use the optimal default arguments for the
# model.
# If a local path is provided, FastVideo will make a best effort
# attempt to identify the optimal arguments.
generator = VideoGenerator.from_pretrained(
"Wan-AI/Wan2.2-I2V-A14B-Diffusers",
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
dit_cpu_offload=True, # DiT need to be offloaded for MoE
vae_cpu_offload=False,
text_encoder_cpu_offload=True,
# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
pin_cpu_memory=True,
# image_encoder_cpu_offload=False,
)
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."
image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
video = generator.generate({
"prompt": prompt,
"inputs": {
"image_path": image_path,
},
"sampling": {
"height": 832,
"width": 480,
"num_frames": 81,
},
"output": {
"output_path": OUTPUT_PATH,
"save_video": True,
},
})
if __name__ == "__main__":
main()