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import gradio as gr
from PIL import Image
import torch
from diffusers import HunyuanVideoPipeline
# ... other imports ...
# Add LORA configuration
LORA_LIST = [
"Top_Off.safetensors",
"huanyan_helper.safetensors",
"huanyan_helper_alpha.safetensors",
"hunyuan-t-solo-v1.0.safetensors",
"stripe_v2.safetensors"
]
def create_advanced_settings():
with gr.Accordion("Advanced Settings", open=False):
# LORA Selection
lora_choices = gr.CheckboxGroup(
choices=LORA_LIST,
label="Select LORAs",
value=[LORA_LIST[0]]
)
lora_weights = {}
for lora in LORA_LIST:
lora_weights[lora] = gr.Slider(0.0, 1.0, value=0.8,
label=f"{lora} Weight")
# Resolution Settings
resolution = gr.Dropdown(
choices=["512x512", "768x768", "1024x1024"],
value="512x512",
label="Output Resolution"
)
return lora_choices, lora_weights, resolution
def validate_image_resolution(image, resolution):
if image is None:
return
img = Image.open(image)
w, h = img.size
if f"{w}x{h}" != resolution:
raise gr.Error(f"Image resolution ({w}x{h}) must match output resolution ({resolution})")
def generate_video(prompt, negative_prompt, lora_choices, lora_weights,
resolution, image_input=None, steps=30):
# Validate image resolution if provided
if image_input:
validate_image_resolution(image_input, resolution)
# Load base model
pipe = HunyuanVideoPipeline.from_pretrained(
"Tencent-Hunyuan/Hunyuan-Video-Lite",
torch_dtype=torch.float16
).to("cuda")
# Apply selected LORAs
for lora in lora_choices:
pipe.load_lora_weights(
f"TTV4ME/{lora}",
adapter_name="hunyuanvideo-lora",
weight_name=lora_weights[lora]
)
# Generate from image or text
if image_input:
image = Image.open(image_input).convert("RGB")
output = pipe.image_to_video(
image,
prompt=prompt,
negative_prompt=negative_prompt,
num_frames=24,
height=int(resolution.split("x")[1]),
width=int(resolution.split("x")[0]),
num_inference_steps=steps
)
else:
output = pipe.text_to_video(
prompt=prompt,
negative_prompt=negative_prompt,
height=int(resolution.split("x")[1]),
width=int(resolution.split("x")[0]),
num_inference_steps=steps
)
return output.video
# Update interface
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt")
negative_prompt = gr.Textbox(label="Negative Prompt")
image_input = gr.Image(label="Input Image", type="filepath")
lora_choices, lora_weights, resolution = create_advanced_settings()
generate_btn = gr.Button("Generate Video")
with gr.Column():
output_video = gr.Video(label="Generated Video")
generate_btn.click(
fn=generate_video,
inputs=[prompt, negative_prompt, lora_choices,
lora_weights, resolution, image_input],
outputs=output_video
)
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