Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,526 Bytes
cc3773d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
import gradio as gr
import tempfile
import json
from inference_focal_length import load_models, run_inference, OmegaConf
import torch
# Initialize models once at startup
cfg = OmegaConf.load("configs/inference_genphoto/adv3_256_384_genphoto_relora_focal_length.yaml")
pipeline, device = load_models(cfg)
def generate_video(base_scene, focal_length_list):
try:
# Validate input
if len(json.loads(focal_length_list)) != 5:
raise ValueError("Exactly 5 focal_length values required")
# Run inference
video_path = run_inference(
pipeline=pipeline,
tokenizer=pipeline.tokenizer,
text_encoder=pipeline.text_encoder,
base_scene=base_scene,
focal_length_list=focal_length_list,
device=device
)
return video_path
except Exception as e:
raise gr.Error(f"Generation failed: {str(e)}")
# Example inputs
examples = [
[
"A small office cubicle with a desk, computer, and chair.",
"[25.1, 36.1, 47.1, 58.1, 69.1]"
],
[
"A large, white couch is placed in a living room, with a mirror above it. The couch is covered with various items, including a blue box, a pink towel, and a pair of shoes.",
"[55.0, 46.0, 37.0, 28.0, 25.0]"
]
]
with gr.Blocks(title="Focal Length Effect Generator") as demo:
gr.Markdown("#Dynamic Focal Length Effect Generation")
with gr.Row():
with gr.Column():
scene_input = gr.Textbox(
label="Scene Description",
placeholder="Describe the scene you want to generate..."
)
focal_length_input = gr.Textbox(
label="Focal Length Values",
placeholder="Enter 5 comma-separated values from 24-70 (e.g., [25.1, 30.2, 33.3, 40.8, 54.0])"
)
submit_btn = gr.Button("Generate Video", variant="primary")
with gr.Column():
video_output = gr.Video(label="Generated Video")
error_output = gr.Textbox(label="Error Messages", visible=False)
gr.Examples(
examples=examples,
inputs=[scene_input, focal_length_input],
outputs=[video_output],
fn=generate_video,
cache_examples=True
)
submit_btn.click(
fn=generate_video,
inputs=[scene_input, focal_length_input],
outputs=[video_output],
)
if __name__ == "__main__":
demo.launch(share=True)
|