Create app_hf.py

app_hf.py

@@ -0,0 +1,123 @@
+import gradio as gr
+import subprocess
+import yaml
+import os
+import cv2
+
+def get_video_frame_count(video_path):
+    if video_path is None:
+        return None
+    
+    video = cv2.VideoCapture(video_path)
+    frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
+    video.release()
+    return frame_count
+
+def initialize_yaml(config_path):
+    try:
+        with open(config_path, 'r') as file:
+            config = yaml.safe_load(file)
+            if config is None:
+                print("YAML file is empty or contains invalid content. Initializing...")
+                config = {'test_cases': {}}
+                with open(config_path, 'w') as outfile:
+                    yaml.safe_dump(config, outfile)
+            else:
+                print("YAML file is valid.")
+    except FileNotFoundError:
+        print("YAML file not found. Creating a new one...")
+        config = {'test_cases': {}}
+        with open(config_path, 'w') as outfile:
+            yaml.safe_dump(config, outfile)
+
+def run_vid2vid(image_path, video_path, width, height, length, seed, cfg, steps):
+    # Assuming the rest of the configuration remains constant
+    config_path = './configs/prompts/animation_facereenac.yaml'
+    
+    # Ensure paths are strings
+    image_path_str = str(image_path)
+    video_path_str = str(video_path)
+    
+    # Load the existing configuration
+    with open(config_path, 'r') as file:
+        config = yaml.safe_load(file)
+    
+    # If the file is somehow still empty or invalid, initialize config
+    if config is None:
+        config = {'test_cases': {}}
+    
+    # Update the configuration using string paths
+    config['test_cases'] = {image_path_str: [video_path_str]}
+    
+    # Save the updated configuration
+    with open(config_path, 'w') as file:
+        yaml.safe_dump(config, file, default_flow_style=False)
+
+    # Construct the command with all the additional arguments
+    command = [
+        "python", "-m", "scripts.vid2vid_gr",
+        "--config", config_path,
+        "-W", str(width),
+        "-H", str(height),
+        # "-L", str(length),
+        "--seed", str(seed),
+        "--cfg", str(cfg),
+        "--steps", str(steps)
+    ]
+    # Conditionally add the "-L" argument if a meaningful value is provided
+    if length is not None:
+        command.extend(["-L", str(length)])
+
+    # Only add "--fps" argument if it is provided (not None)
+    # if fps is not None:
+    #     command.extend(["--fps", str(fps)])
+
+    # Run the vid2vid script with the specified parameters
+    subprocess.run(command)
+    
+    # Assuming the script saves its output to a known, fixed path
+    output_file_path = "output/result/result.mp4"
+    
+    # Return this path for Gradio to display the video
+    return output_file_path
+
+with gr.Blocks(title="AniPortrait") as blocks_app:
+    gr.Markdown("# Gradio UI for AniPortrait vid2vid")
+    gr.Markdown("Audio-Driven Synthesis of Photorealistic Portrait Animation")
+    gr.Markdown("Original Project: https://github.com/Zejun-Yang/AniPortrait")
+    
+    with gr.Row():
+        image_input = gr.Image(type="filepath", label="Upload Image")
+        video_input = gr.Video(label="Upload Video")
+        
+    with gr.Row():
+        width = gr.Slider(minimum=256, maximum=1024, step=8, value=512, label="Width (-W)")
+        height = gr.Slider(minimum=256, maximum=1024, step=8, value=512, label="Height (-H)")
+        
+    with gr.Row():
+        length = gr.Number(value=None, label="Length (-L)")
+        seed = gr.Number(value=42, label="Seed (--seed)")
+    video_input.change(get_video_frame_count, inputs=video_input, outputs=length)
+    
+    with gr.Row():
+        cfg = gr.Slider(minimum=0.1, maximum=10.0, step=0.1, value=3.5, label="Cfg (--cfg)")
+        steps = gr.Slider(minimum=1, maximum=100.0, step=1, value=25, label="Steps (--steps)")
+        
+    # with gr.Row():
+    #     fps = gr.Number(label="FPS (--fps)")
+        
+    output_video = gr.PlayableVideo(label="Result")
+
+    def process_and_display(image_path, video_path, width, height, length, seed, cfg, steps):
+        return run_vid2vid(image_path, video_path, width, height, length, seed, cfg, steps)
+    
+    run_button = gr.Button("Run")
+    run_button.click(
+        process_and_display, 
+        inputs=[image_input, video_input, width, height, length, seed, cfg, steps],
+        outputs=output_video
+    )
+
+if __name__ == "__main__":
+    blocks_app.queue(max_size=3).launch(share=False, show_error=True, show_api=False)
+