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| import gradio as gr | |
| import time | |
| import random | |
| import numpy as np | |
| from PIL import Image | |
| import io | |
| import base64 | |
| from typing import Tuple, Optional | |
| def generate_video_from_text( | |
| prompt: str, | |
| duration: int = 5, | |
| style: str = "realistic", | |
| quality: str = "high", | |
| motion_strength: float = 0.5, | |
| seed: Optional[int] = None | |
| ) -> str: | |
| """ | |
| Generate a video from text prompt using simulated WAN model. | |
| Args: | |
| prompt: Text description of the video to generate | |
| duration: Video duration in seconds | |
| style: Video style (realistic, artistic, anime, cartoon) | |
| quality: Video quality (low, medium, high) | |
| motion_strength: Strength of motion in video (0.0 to 1.0) | |
| seed: Random seed for reproducible generation | |
| Returns: | |
| Path to generated video file | |
| """ | |
| if not prompt.strip(): | |
| raise gr.Error("Please enter a text prompt to generate a video.") | |
| # Simulate video generation process | |
| progress_steps = [ | |
| "Analyzing prompt...", | |
| "Generating keyframes...", | |
| "Applying style transfer...", | |
| "Creating motion vectors...", | |
| "Rendering video...", | |
| "Post-processing...", | |
| "Finalizing video..." | |
| ] | |
| for i, step in enumerate(progress_steps): | |
| time.sleep(0.5) # Simulate processing time | |
| if i == len(progress_steps) - 1: | |
| yield f"β {step}" | |
| else: | |
| yield f"β³ {step}" | |
| # Generate a placeholder video (in real implementation, this would call WAN API) | |
| # For demo purposes, we'll create a simple animated frame sequence | |
| frames = [] | |
| num_frames = duration * 10 # 10 fps | |
| if seed is None: | |
| seed = random.randint(0, 999999) | |
| np.random.seed(seed) | |
| # Create simple animated frames based on prompt | |
| for i in range(num_frames): | |
| # Generate a frame with some motion | |
| width, height = 512, 512 | |
| frame = np.zeros((height, width, 3), dtype=np.uint8) | |
| # Create gradient background | |
| for y in range(height): | |
| for x in range(width): | |
| frame[y, x, 0] = int(255 * (x / width) * (1 + 0.3 * np.sin(i * 0.1))) | |
| frame[y, x, 1] = int(255 * (y / height) * (1 + 0.3 * np.cos(i * 0.1))) | |
| frame[y, x, 2] = int(128 + 127 * np.sin((x + y + i * 10) * 0.01)) | |
| # Add some moving elements based on prompt | |
| center_x = width // 2 + int(100 * np.sin(i * 0.05) * motion_strength) | |
| center_y = height // 2 + int(100 * np.cos(i * 0.05) * motion_strength) | |
| cv2 = __import__('cv2') | |
| cv2.circle(frame, (center_x, center_y), 50, (255, 255, 255), -1) | |
| frames.append(Image.fromarray(frame)) | |
| # Save frames as a video (placeholder - in real implementation, return actual video) | |
| # For demo, we'll return a sample video URL | |
| sample_videos = { | |
| "realistic": "https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_1mb.mp4", | |
| "artistic": "https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_2mb.mp4", | |
| "anime": "https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_5mb.mp4", | |
| "cartoon": "https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_1mb.mp4" | |
| } | |
| return sample_videos.get(style, sample_videos["realistic"]) | |
| def generate_video_from_image( | |
| image: np.ndarray, | |
| prompt: str, | |
| duration: int = 5, | |
| motion_strength: float = 0.5, | |
| seed: Optional[int] = None | |
| ) -> str: | |
| """ | |
| Generate a video from an image with text prompt for motion. | |
| Args: | |
| image: Input image as numpy array | |
| prompt: Text description of desired motion/animation | |
| duration: Video duration in seconds | |
| motion_strength: Strength of motion in video (0.0 to 1.0) | |
| seed: Random seed for reproducible generation | |
| Returns: | |
| Path to generated video file | |
| """ | |
| if image is None: | |
| raise gr.Error("Please upload an image to generate a video.") | |
| if not prompt.strip(): | |
| raise gr.Error("Please describe the motion you want to add to the image.") | |
| # Simulate processing | |
| progress_steps = [ | |
| "Analyzing image...", | |
| "Extracting features...", | |
| "Generating motion from prompt...", | |
| "Creating video frames...", | |
| "Applying motion blur...", | |
| "Rendering final video..." | |
| ] | |
| for step in progress_steps: | |
| time.sleep(0.6) | |
| # Return sample video for demo | |
| return "https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_2mb.mp4" | |
| def create_custom_css() -> str: | |
| """Create custom CSS for the application.""" | |
| return """ | |
| .gradio-container { | |
| max-width: 1200px !important; | |
| margin: auto !important; | |
| } | |
| .main-header { | |
| text-align: center; | |
| margin-bottom: 2rem; | |
| padding: 1.5rem; | |
| background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); | |
| border-radius: 15px; | |
| color: white; | |
| } | |
| .generation-card { | |
| border: 2px solid #e5e7eb; | |
| border-radius: 15px; | |
| padding: 1.5rem; | |
| margin: 1rem 0; | |
| background: white; | |
| box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); | |
| } | |
| .progress-container { | |
| margin: 1rem 0; | |
| padding: 1rem; | |
| background: #f3f4f6; | |
| border-radius: 10px; | |
| font-family: monospace; | |
| } | |
| .example-prompt { | |
| cursor: pointer; | |
| padding: 0.5rem; | |
| margin: 0.25rem; | |
| background: #f9fafb; | |
| border: 1px solid #e5e7eb; | |
| border-radius: 8px; | |
| transition: all 0.2s; | |
| } | |
| .example-prompt:hover { | |
| background: #ede9fe; | |
| border-color: #8b5cf6; | |
| } | |
| """ | |
| # Create the custom theme | |
| custom_theme = gr.themes.Soft( | |
| primary_hue="purple", | |
| secondary_hue="indigo", | |
| neutral_hue="slate", | |
| font=gr.themes.GoogleFont("Inter"), | |
| text_size="lg", | |
| spacing_size="lg", | |
| radius_size="md" | |
| ).set( | |
| button_primary_background_fill="*primary_600", | |
| button_primary_background_fill_hover="*primary_700", | |
| block_title_text_weight="600", | |
| block_border_width="2px", | |
| block_border_color="*neutral_200", | |
| ) | |
| # Gradio 6: NO parameters in gr.Blocks() constructor! | |
| with gr.Blocks() as demo: | |
| # Header | |
| gr.HTML(""" | |
| <div class="main-header"> | |
| <h1>π¬ WAN Video Generator</h1> | |
| <p>Transform your ideas into stunning videos with advanced AI technology</p> | |
| <p style="font-size: 0.9rem; margin-top: 0.5rem;"> | |
| Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color: white; text-decoration: underline;">anycoder</a> | |
| </p> | |
| </div> | |
| """) | |
| with gr.Tabs() as tabs: | |
| # Text to Video Tab | |
| with gr.TabItem("π Text to Video", elem_id="text-to-video"): | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| gr.Markdown("### π― Generate Video from Text") | |
| prompt_input = gr.Textbox( | |
| label="Video Description", | |
| placeholder="Describe the video you want to generate... (e.g., 'A serene beach with waves gently lapping at sunset')", | |
| lines=3, | |
| max_lines=5 | |
| ) | |
| with gr.Row(): | |
| duration_slider = gr.Slider( | |
| minimum=2, | |
| maximum=30, | |
| value=5, | |
| step=1, | |
| label="Duration (seconds)" | |
| ) | |
| motion_slider = gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.5, | |
| step=0.1, | |
| label="Motion Strength" | |
| ) | |
| with gr.Row(): | |
| style_dropdown = gr.Dropdown( | |
| choices=["realistic", "artistic", "anime", "cartoon"], | |
| value="realistic", | |
| label="Video Style" | |
| ) | |
| quality_dropdown = gr.Dropdown( | |
| choices=["low", "medium", "high"], | |
| value="high", | |
| label="Quality" | |
| ) | |
| seed_input = gr.Number( | |
| label="Seed (optional)", | |
| placeholder="Leave blank for random", | |
| precision=0 | |
| ) | |
| generate_btn = gr.Button( | |
| "π¬ Generate Video", | |
| variant="primary", | |
| size="lg" | |
| ) | |
| with gr.Column(scale=1): | |
| gr.Markdown("### π‘ Example Prompts") | |
| example_prompts = [ | |
| "A majestic eagle soaring through mountain peaks at sunrise", | |
| "A bustling city street with neon lights reflecting on wet pavement", | |
| "A peaceful garden with butterflies fluttering around colorful flowers", | |
| "An astronaut floating in space with Earth in the background", | |
| "A cozy fireplace crackling on a snowy winter evening" | |
| ] | |
| for prompt in example_prompts: | |
| gr.HTML(f'<div class="example-prompt" onclick="document.querySelector(\'[data-testid=\"textbox\"]\').value = `{prompt}`">{prompt}</div>') | |
| gr.Markdown("### βοΈ Tips") | |
| gr.Markdown(""" | |
| β’ Be descriptive but concise | |
| β’ Include setting and mood | |
| β’ Specify camera movements if needed | |
| β’ Use seeds for reproducible results | |
| """) | |
| # Progress and Output | |
| progress_text = gr.Textbox( | |
| label="Generation Progress", | |
| interactive=False, | |
| visible=False | |
| ) | |
| with gr.Column(elem_classes="generation-card"): | |
| gr.Markdown("### πΉ Generated Video") | |
| video_output = gr.Video( | |
| label="Your Generated Video", | |
| visible=False, | |
| height=400 | |
| ) | |
| # Event handlers - Fixed for Gradio 6 | |
| def handle_generate_text(prompt, duration, style, quality, motion, seed): | |
| if not prompt.strip(): | |
| raise gr.Error("Please enter a prompt!") | |
| # Show progress | |
| progress_updates = [] | |
| # Generate video with progress updates | |
| for progress in generate_video_from_text(prompt, duration, style, quality, motion, seed): | |
| if isinstance(progress, str): | |
| progress_updates.append(progress) | |
| yield { | |
| progress_text: gr.Textbox(value=progress, visible=True), | |
| video_output: gr.Video(visible=False) | |
| } | |
| # Show result | |
| video_url = generate_video_from_text(prompt, duration, style, quality, motion, seed) | |
| if isinstance(video_url, str): | |
| yield { | |
| video_output: gr.Video(value=video_url, visible=True), | |
| progress_text: gr.Textbox(value="β Video generated successfully!", visible=True) | |
| } | |
| generate_btn.click( | |
| fn=handle_generate_text, | |
| inputs=[prompt_input, duration_slider, style_dropdown, quality_dropdown, motion_slider, seed_input], | |
| outputs=[progress_text, video_output], | |
| api_visibility="public" | |
| ) | |
| # Image to Video Tab | |
| with gr.TabItem("πΌοΈ Image to Video", elem_id="image-to-video"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("### π¨ Animate Your Image") | |
| image_input = gr.Image( | |
| label="Upload Image", | |
| type="numpy", | |
| height=300 | |
| ) | |
| motion_prompt = gr.Textbox( | |
| label="Motion Description", | |
| placeholder="Describe how you want the image to move... (e.g., 'Make the clouds drift slowly and the water ripple')", | |
| lines=2 | |
| ) | |
| with gr.Row(): | |
| img_duration_slider = gr.Slider( | |
| minimum=2, | |
| maximum=20, | |
| value=5, | |
| step=1, | |
| label="Duration (seconds)" | |
| ) | |
| img_motion_slider = gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.5, | |
| step=0.1, | |
| label="Motion Strength" | |
| ) | |
| img_seed_input = gr.Number( | |
| label="Seed (optional)", | |
| precision=0 | |
| ) | |
| img_generate_btn = gr.Button( | |
| "π¬ Animate Image", | |
| variant="primary", | |
| size="lg" | |
| ) | |
| with gr.Column(): | |
| gr.Markdown("### π― Best Practices") | |
| gr.Markdown(""" | |
| β’ Use high-quality images for best results | |
| β’ Describe motion clearly and specifically | |
| β’ Start with lower motion strength | |
| β’ Images with clear subjects work better | |
| β’ Landscape orientation recommended | |
| """) | |
| gr.Markdown("### π‘ Motion Examples") | |
| gr.Markdown(""" | |
| β’ "Gentle swaying of trees in the wind" | |
| β’ "Water flowing and rippling" | |
| β’ "Clouds moving across the sky" | |
| β’ "Leaves falling from trees" | |
| β’ "Fire flickering and dancing" | |
| """) | |
| img_progress_text = gr.Textbox( | |
| label="Generation Progress", | |
| interactive=False, | |
| visible=False | |
| ) | |
| img_video_output = gr.Video( | |
| label="Your Animated Video", | |
| visible=False, | |
| height=400 | |
| ) | |
| img_generate_btn.click( | |
| fn=generate_video_from_image, | |
| inputs=[image_input, motion_prompt, img_duration_slider, img_motion_slider, img_seed_input], | |
| outputs=[img_video_output, img_progress_text], | |
| api_visibility="public" | |
| ) | |
| # Gallery Tab | |
| with gr.TabItem("π Gallery", elem_id="gallery"): | |
| gr.Markdown("### π Featured Generations") | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Video( | |
| label="Ocean Waves", | |
| value="https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_1mb.mp4", | |
| height=250 | |
| ) | |
| gr.Markdown("**Ocean Waves** - 'Peaceful ocean waves crashing on a sandy beach'") | |
| with gr.Column(): | |
| gr.Video( | |
| label="Forest Path", | |
| value="https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_2mb.mp4", | |
| height=250 | |
| ) | |
| gr.Markdown("**Forest Path** - 'A misty forest path with sunlight filtering through trees'") | |
| with gr.Column(): | |
| gr.Video( | |
| label="City Lights", | |
| value="https://sample-videos.com/zip/10/mp4/SampleVideo_1280x720_5mb.mp4", | |
| height=250 | |
| ) | |
| gr.Markdown("**City Lights** - 'Neon city lights at night with traffic flowing'") | |
| gr.Markdown("### π Generation Statistics") | |
| gr.DataFrame( | |
| value=[ | |
| ["Total Videos Generated", "1,234,567"], | |
| ["Average Generation Time", "45 seconds"], | |
| ["Most Popular Style", "Realistic"], | |
| ["Average Duration", "8 seconds"], | |
| ["Success Rate", "98.5%"] | |
| ], | |
| headers=["Metric", "Value"], | |
| datatype=["str", "str"], | |
| interactive=False | |
| ) | |
| # Gradio 6: ALL app parameters go in launch()! | |
| demo.launch( | |
| theme=custom_theme, | |
| css=create_custom_css(), | |
| footer_links=[ | |
| {"label": "Documentation", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}, | |
| {"label": "GitHub", "url": "https://github.com/gradio-app/gradio"}, | |
| {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"} | |
| ] | |
| ) |