import gradio as gr import time import random import os def generate_video_from_image( image, prompt, negative_prompt, num_frames, guidance_scale, inference_steps, seed, use_spicy_mode, spicy_intensity, progress=gr.Progress() ): """Simulate video generation from image using Wan 2.2 model with spicy settings""" # Validate inputs if image is None: raise gr.Error("Please upload an image to generate a video.") if not prompt.strip(): raise gr.Error("Please enter a prompt for your video generation.") # Set seed for reproducibility if seed == -1: seed = random.randint(0, 2147483647) # Simulate processing steps progress(0, desc="Initializing Wan 2.2 Spicy mode...") time.sleep(0.5) progress(0.1, desc="Loading model components...") time.sleep(0.8) progress(0.2, desc="Preparing image embeddings...") time.sleep(0.6) # Simulate video generation progress progress(0.3, desc=f"Running {inference_steps} inference steps...") for i in range(1, inference_steps + 1): time.sleep(0.15) progress_rate = 0.3 + (i / inference_steps) * 0.6 progress(progress_rate, desc=f"Step {i}/{inference_steps} completed...") # Apply spicy mode effects if use_spicy_mode: progress(0.9, desc=f"Applying spicy mode with intensity {spicy_intensity}...") time.sleep(1.2) progress(1.0, desc="Finalizing video output...") time.sleep(0.3) # Create a fake video file path (in a real app, this would be the generated video) # For demo purposes, we'll use a placeholder video video_path = "https://gradio-builds.s3.amazonaws.com/assets/cheetah-003.jpg" return { "video": video_path, "stats": f"✅ Video generated successfully!\n\n" f"• Prompt: {prompt}\n" f"• Frames: {num_frames}\n" f"• Guidance Scale: {guidance_scale}\n" f"• Inference Steps: {inference_steps}\n" f"• Seed: {seed}\n" f"• Spicy Mode: {'Enabled' if use_spicy_mode else 'Disabled'}\n" f"• Spicy Intensity: {spicy_intensity if use_spicy_mode else 'N/A'}" } # Create the Gradio interface with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo", secondary_hue="purple")) as demo: # Header with title and description gr.Markdown( """

Wan 2.2 Spicy Image-to-Video Generator

Transform your images into stunning videos using the advanced Wan 2.2 model with spicy enhancements. Perfect for creative content, animations, and visual storytelling.

Built with anycoder
""" ) with gr.Row(): with gr.Column(scale=1): # Input section gr.Markdown("### 🎨 Input Settings") image_input = gr.Image( label="Upload Image", type="pil", height=300, sources=["upload", "webcam", "clipboard"] ) prompt_input = gr.Textbox( label="Prompt", placeholder="Describe the video you want to generate (e.g., 'A cat walking in a garden with阳光, cinematic, high quality')", lines=3 ) negative_prompt = gr.Textbox( label="Negative Prompt", placeholder="Elements to avoid in the video (e.g., 'blurry, low quality, distorted')", lines=2 ) with gr.Accordion("Advanced Settings", open=False): num_frames = gr.Slider( label="Number of Frames", minimum=8, maximum=64, value=24, step=1, info="Number of frames in the generated video" ) guidance_scale = gr.Slider( label="Guidance Scale", minimum=1.0, maximum=20.0, value=7.5, step=0.5, info="How closely the video follows your prompt" ) inference_steps = gr.Slider( label="Inference Steps", minimum=10, maximum=100, value=30, step=5, info="Number of denoising steps (higher = better quality but slower)" ) seed = gr.Number( label="Seed", value=-1, precision=0, info="Set to -1 for random seed" ) with gr.Accordion("🔥 Spicy Mode Settings", open=True): use_spicy_mode = gr.Checkbox( label="Enable Spicy Mode", value=True, info="Activate enhanced generation with spicy effects" ) spicy_intensity = gr.Slider( label="Spicy Intensity", minimum=1, maximum=10, value=7, step=1, info="How spicy should the video be? (1-10)" ) spicy_effects = gr.CheckboxGroup( label="Spicy Effects", choices=[ "Fast Motion", "High Contrast", "Color Boost", "Dynamic Transitions", "Enhanced Details", "Cinematic Effects" ], value=["High Contrast", "Color Boost", "Dynamic Transitions"], info="Select which spicy effects to apply" ) generate_btn = gr.Button( "🎬 Generate Video", variant="primary", size="lg" ) with gr.Column(scale=1): # Output section gr.Markdown("### 🎥 Generated Output") video_output = gr.Video( label="Generated Video", height=400, autoplay=True ) stats_output = gr.Textbox( label="Generation Statistics", lines=10, show_copy_button=True ) # Examples gr.Markdown("### 💡 Examples") with gr.Row(): example1_btn = gr.Button("Nature Scene") example2_btn = gr.Button("Urban Motion") example3_btn = gr.Button("Abstract Art") # Example functions def set_example1(): return { prompt_input: "A serene landscape with flowing river and mountains at sunset, cinematic lighting", use_spicy_mode: True, spicy_intensity: 6, spicy_effects: ["Color Boost", "Cinematic Effects"] } def set_example2(): return { prompt_input: "Time-lapse of city streets at night with neon lights and moving cars, cyberpunk style", use_spicy_mode: True, spicy_intensity: 8, spicy_effects: ["Fast Motion", "High Contrast", "Color Boost"] } def set_example3(): return { prompt_input: "Abstract fluid art with vibrant colors swirling and merging, macro perspective", use_spicy_mode: False, spicy_intensity: 3, spicy_effects: ["Enhanced Details"] } example1_btn.click(set_example1, outputs=[prompt_input, use_spicy_mode, spicy_intensity, spicy_effects]) example2_btn.click(set_example2, outputs=[prompt_input, use_spicy_mode, spicy_intensity, spicy_effects]) example3_btn.click(set_example3, outputs=[prompt_input, use_spicy_mode, spicy_intensity, spicy_effects]) # Footer with information gr.Markdown( """

About This Demo

This application uses the Wan 2.2 model with spicy enhancements to generate videos from images.

Spicy Mode applies creative enhancements like enhanced colors, dynamic transitions, and more.

Note: This is a demonstration. In a real implementation, the video would be generated by the Wan 2.2 model.

""" ) # Event listener for generate button generate_btn.click( fn=generate_video_from_image, inputs=[ image_input, prompt_input, negative_prompt, num_frames, guidance_scale, inference_steps, seed, use_spicy_mode, spicy_intensity ], outputs=[video_output, stats_output], api_visibility="public" ) # Launch the app with modern theme demo.launch( theme=gr.themes.Soft(primary_hue="indigo", secondary_hue="purple"), footer_links=[{"label": "Wan 2.2 Model", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}] )