Update app.py from anycoder

app.py

@@ -1,111 +1,161 @@
-import gradio as gr
+<|begin_of_box|>import gradio as gr
+import numpy as np
+import cv2
+import tempfile
+import os
+from PIL import Image
 import time
-from utils import calculate_similarity_mock
 
-# Define the main processing function
-def compare_audio(target_audio, url_1, url_2):
+# Simulated outpainting function (in a real application, this would use a proper model)
+def outpaint_video_with_reference(input_video, reference_image, outpaint_ratio=0.5):
     """
-    Takes a target audio file path and two URLs.
-    Returns a dictionary of similarity scores.
+    Simulate video outpainting to match reference image height.
+    In a real implementation, this would use a diffusion model or similar.
     """
-    if target_audio is None:
-        raise gr.Error("Please upload a target audio file first.")
-    
-    if not url_1 or not url_2:
-        raise gr.Warning("Please provide both source URLs for comparison.")
-
-    # In a real app, you would download the audio from the URLs here
-    # and run them through a model like CLAP or Wav2Vec.
-    # We are using a simulated backend for this demo.
-    
-    results = calculate_similarity_mock(target_audio, url_1, url_2)
-    
-    # Return the results for the Label component
-    return results
+    try:
+        # Create temporary files for processing
+        with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as temp_video:
+            temp_video_path = temp_video.name
+        
+        with tempfile.NamedTemporaryFile(suffix='.png', delete=False) as temp_ref:
+            temp_ref_path = temp_ref.name
+        
+        # Save uploaded files
+        with open(input_video, 'wb') as f:
+            f.write(open(input_video, 'rb').read())
+        
+        with open(reference_image, 'wb') as f:
+            f.write(open(reference_image, 'rb').read())
+        
+        # Get video and reference image dimensions
+        cap = cv2.VideoCapture(input_video)
+        ref_img = Image.open(reference_image)
+        ref_height = ref_img.height
+        ref_width = ref_img.width
+        
+        # Get original video dimensions
+        original_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+        original_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+        
+        # Calculate new dimensions to match reference height
+        new_height = ref_height
+        scale_factor = new_height / original_height
+        new_width = int(original_width * scale_factor)
+        
+        # Create output video writer
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        out = cv2.VideoWriter(temp_video_path, fourcc, 30.0, (new_width, new_height))
+        
+        frame_count = 0
+        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        
+        while cap.isOpened():
+            ret, frame = cap.read()
+            if not ret:
+                break
+            
+            # Resize frame to match new dimensions
+            resized_frame = cv2.resize(frame, (new_width, new_height))
+            
+            # Simulate outpainting by adding a border that matches reference style
+            # In a real implementation, this would use AI to generate content
+            border_size = int(new_width * outpaint_ratio)
+            if border_size > 0:
+                # Create a border that tries to match the reference image style
+                border_color = np.mean(resized_frame, axis=(0, 1))
+                bordered_frame = cv2.copyMakeBorder(
+                    resized_frame,
+                    0, 0, border_size, border_size,
+                    cv2.BORDER_CONSTANT,
+                    value=border_color
+                )
+                out.write(bordered_frame)
+            else:
+                out.write(resized_frame)
+            
+            frame_count += 1
+            if frame_count % 10 == 0:
+                yield f"Processing frame {frame_count}/{total_frames}..."
+        
+        cap.release()
+        out.release()
+        
+        # Return the processed video
+        yield temp_video_path
+        
+    except Exception as e:
+        yield f"Error: {str(e)}"
+    finally:
+        # Clean up temporary files
+        try:
+            if 'temp_video_path' in locals() and os.path.exists(temp_video_path):
+                os.unlink(temp_video_path)
+            if 'temp_ref_path' in locals() and os.path.exists(temp_ref_path):
+                os.unlink(temp_ref_path)
+        except:
+            pass
 
-# Create the Gradio 6 Application
-# 🚨 NOTE: gr.Blocks() takes NO arguments in Gradio 6. 
-# Theme and title go in demo.launch()
+# Create the Gradio interface
 with gr.Blocks() as demo:
+    gr.Markdown("# 🎬 Video Outpainting with Reference Height Matching")
+    gr.Markdown("Upload a video and a reference image. The video will be outpainted to match the height of the reference image.")
     
-    # Header Section
     with gr.Row():
         with gr.Column():
-            gr.Markdown("# 🎵 Audio Similarity Matcher")
-            gr.Markdown(
-                "Upload a target sound and compare it against two source audio URLs to find the best match. "
-                "[Built with anycoder](https://huggingface.co/spaces/akhaliq/anycoder)"
-            )
-
-    # Main Content
-    with gr.Row():
-        # Left Column: Inputs
-        with gr.Column(scale=1):
-            gr.Markdown("### 1. Target Audio")
-            target_input = gr.Audio(
-                sources=["upload", "microphone"],
-                type="filepath",
-                label="Upload Target Sound",
-                render=True
-            )
+            gr.Markdown("### Input Video")
+            video_input = gr.Video(label="Upload Video", type="filepath")
+            gr.Markdown("### Reference Image")
+            reference_input = gr.Image(label="Upload Reference Image", type="filepath")
             
-            gr.Markdown("### 2. Compare Against Source URLs")
-            url_input_1 = gr.Textbox(
-                label="Source Audio URL #1",
-                placeholder="https://example.com/audio1.mp3",
-                lines=1
-            )
-            url_input_2 = gr.Textbox(
-                label="Source Audio URL #2",
-                placeholder="https://example.com/audio2.mp3",
-                lines=1
+            outpaint_ratio = gr.Slider(
+                minimum=0.1,
+                maximum=1.0,
+                value=0.3,
+                step=0.1,
+                label="Outpaint Ratio (percentage of new width)"
             )
             
-            submit_btn = gr.Button("Analyze Similarity 🚀", variant="primary", size="lg")
-
-        # Right Column: Outputs
-        with gr.Column(scale=1):
-            gr.Markdown("### Results")
-            # Label component is great for classification/similarity scores
-            similarity_output = gr.Label(
-                label="Similarity Score",
-                num_top_classes=2
-            )
+            process_button = gr.Button("Process Video", variant="primary")
             
-            # JSON output for detailed debugging data
-            json_output = gr.JSON(
-                label="Detailed Analysis Data",
-                visible=False
-            )
-
-    # Event Listeners
-    # 🚨 Gradio 6 uses 'api_visibility' instead of just api_name
-    submit_btn.click(
-        fn=compare_audio,
-        inputs=[target_input, url_input_1, url_input_2],
-        outputs=[similarity_output],
+        with gr.Column():
+            gr.Markdown("### Output")
+            output_video = gr.Video(label="Processed Video")
+            status_text = gr.Textbox(label="Status", interactive=False)
+    
+    # Process function
+    def process_video(video, reference, ratio):
+        if not video or not reference:
+            return None, "Please upload both video and reference image"
+        
+        status_text = ""
+        for status in outpaint_video_with_reference(video, reference, ratio):
+            if isinstance(status, str):
+                status_text = status
+                yield None, status_text
+            else:
+                yield status, "Processing complete!"
+    
+    process_button.click(
+        fn=process_video,
+        inputs=[video_input, reference_input, outpaint_ratio],
+        outputs=[output_video, status_text],
         api_visibility="public"
     )
 
-    # Add example data to help users test quickly
-    gr.Examples(
-        examples=[
-            [None, "https://www2.cs.uic.edu/~i101/SoundFiles/BabyElephantWalk60.wav", "https://www2.cs.uic.edu/~i101/SoundFiles/CantinaBand3.wav"]
-        ],
-        inputs=[target_input, url_input_1, url_input_2]
-    )
-
-# Launch the application
-# 🚨 CRITICAL: Theme, CSS, and app configs go here in Gradio 6
-if __name__ == "__main__":
-    demo.launch(
-        theme=gr.themes.Soft(
-            primary_hue="indigo",
-            secondary_hue="blue",
-            neutral_hue="slate",
-            radius_size="lg"
-        ),
-        footer_links=[
-            {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}
-        ]
-    )
+# Launch the app with modern theme
+demo.launch(
+    theme=gr.themes.Soft(
+        primary_hue="blue",
+        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",
+    ),
+    footer_links=[{"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}]
+)<|end_of_box|>