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import gradio as gr
from huggingface_hub import hf_hub_download
import subprocess
import tempfile
import shutil
import os
import spaces
def download_model(repo_id, model_name):
model_path = hf_hub_download(repo_id=repo_id, filename=model_name)
return model_path
@spaces.GPU
def run_inference(model_name, prompt_text):
repo_id = "hpcai-tech/Open-Sora"
# Map model names to their respective configuration files
config_mapping = {
"OpenSora-v1-16x256x256.pth": "configs/opensora/inference/16x256x256.py",
"OpenSora-v1-HQ-16x256x256.pth": "configs/opensora/inference/16x512x512.py",
"OpenSora-v1-HQ-16x512x512.pth": "configs/opensora/inference/64x512x512.py"
}
config_path = config_mapping[model_name]
ckpt_path = download_model(repo_id, model_name)
# Save prompt_text to a temporary text file
prompt_file = tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode='w')
prompt_file.write(prompt_text)
prompt_file.close()
# Read and update the configuration file
with open(config_path, 'r') as file:
config_content = file.read()
config_content = config_content.replace('prompt_path = "./assets/texts/t2v_samples.txt"', f'prompt_path = "{prompt_file.name}"')
with tempfile.NamedTemporaryFile('w', delete=False) as temp_file:
temp_file.write(config_content)
temp_config_path = temp_file.name
cmd = [
"torchrun", "--standalone", "--nproc_per_node", "1",
"scripts/inference.py", temp_config_path,
"--ckpt-path", ckpt_path
]
result = subprocess.run(cmd, capture_output=True, text=True)
# Clean up the temporary files
os.remove(temp_file.name)
os.remove(prompt_file.name)
if result.returncode == 0:
# Assuming the output video is saved at a known location, for example "./output/video.mp4"
output_video_path = "./output/video.mp4"
return output_video_path
else:
print("Error occurred:", result.stderr)
return None # You might want to handle errors differently
def main():
gr.Interface(
fn=run_inference,
inputs=[
gr.Dropdown(choices=[
"OpenSora-v1-16x256x256.pth",
"OpenSora-v1-HQ-16x256x256.pth",
"OpenSora-v1-HQ-16x512x512.pth"
], label="Model Selection"),
gr.Textbox(label="Prompt Text", placeholder="Enter prompt text here")
],
outputs=gr.Video(label="Output Video"),
title="Open-Sora Inference",
description="Run Open-Sora Inference with Custom Parameters",
).launch()
if __name__ == "__main__":
main()
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