Update app.py

app.py

@@ -1,5 +1,5 @@
 # -*- coding:UTF-8 -*-
-# !/usr/bin/env python
+#!/usr/bin/env python
 import spaces
 import numpy as np
 import gradio as gr
@@ -18,47 +18,87 @@ import onnxruntime as ort
 import cv2
 from roop.face_analyser import get_one_face
 
+# Set up the application theme and styling
+custom_css = """
+.gradio-container {
+    font-family: 'Arial', sans-serif;
+}
+.disclaimer {
+    background-color: #f8d7da;
+    border: 1px solid #f5c6cb;
+    color: #721c24;
+    padding: 10px;
+    margin-bottom: 20px;
+    border-radius: 5px;
+}
+.instructions {
+    background-color: #e2f0d9;
+    border: 1px solid #c5e0b4;
+    padding: 10px;
+    margin-bottom: 20px;
+    border-radius: 5px;
+}
+"""
+
 @spaces.GPU
 def swap_face(source_file, target_file, doFaceEnhancer):
-    session_dir = "temp"  # Sử dụng thư mục cố định
+    """
+    Swap faces between source and target images.
+    
+    Args:
+        source_file: Image containing the face to be used
+        target_file: Image where the face will be swapped onto
+        doFaceEnhancer: Whether to enhance the resulting face
+        
+    Returns:
+        Path to the output image with the swapped face
+    """
+    # Create a temporary directory for processing
+    session_dir = "temp"
     os.makedirs(session_dir, exist_ok=True)
-
-    # Tạo tên file ngẫu nhiên
+    
+    # Generate random filenames to avoid conflicts
     source_filename = f"source_{random.randint(1000, 9999)}.jpg"
     target_filename = f"target_{random.randint(1000, 9999)}.jpg"
     output_filename = f"output_{random.randint(1000, 9999)}.jpg"
-
+    
+    # Save uploaded images to the temporary directory
     source_path = os.path.join(session_dir, source_filename)
     target_path = os.path.join(session_dir, target_filename)
-
+    
     source_image = Image.fromarray(source_file)
     source_image.save(source_path)
+    
     target_image = Image.fromarray(target_file)
     target_image.save(target_path)
-
-    print("source_path: ", source_path)
-    print("target_path: ", target_path)
-
+    
+    print("Processing source image:", source_path)
+    print("Processing target image:", target_path)
+    
     # Check if a face is detected in the source image
     source_face = get_one_face(cv2.imread(source_path))
     if source_face is None:
-        raise gradio.exceptions.Error("No face in source path detected.")
-
+        raise gradio.exceptions.Error("No face detected in the source image. Please upload a clear photo with a face.")
+    
     # Check if a face is detected in the target image
     target_face = get_one_face(cv2.imread(target_path))
     if target_face is None:
-        raise gradio.exceptions.Error("No face in target path detected.")
-
+        raise gradio.exceptions.Error("No face detected in the target image. Please upload a clear photo with a face.")
+    
+    # Set up output path
     output_path = os.path.join(session_dir, output_filename)
     normalized_output_path = normalize_output_path(source_path, target_path, output_path)
-
+    
+    # Determine which processors to use
     frame_processors = ["face_swapper", "face_enhancer"] if doFaceEnhancer else ["face_swapper"]
-
+    
+    # Validate processors
     for frame_processor in get_frame_processors_modules(frame_processors):
         if not frame_processor.pre_check():
             print(f"Pre-check failed for {frame_processor}")
-            raise gradio.exceptions.Error(f"Pre-check failed for {frame_processor}")
-
+            raise gradio.exceptions.Error(f"The {frame_processor} module failed to initialize. Please try again.")
+    
+    # Configure roop settings
     roop.globals.source_path = source_path
     roop.globals.target_path = target_path
     roop.globals.output_path = normalized_output_path
@@ -76,16 +116,79 @@ def swap_face(source_file, target_file, doFaceEnhancer):
     roop.globals.max_memory = 60
     roop.globals.execution_threads = 8
     
+    # Start the face swapping process
     start()
+    
     return normalized_output_path
 
-app = gr.Interface(
-    fn=swap_face, 
-    inputs=[
-        gr.Image(), 
-        gr.Image(), 
-        gr.Checkbox(label="Face Enhancer?", info="Do face enhancement?")
-    ], 
-    outputs="image"
-)
+# Create the Gradio interface with improved descriptions and layout
+with gr.Blocks(css=custom_css) as app:
+    gr.Markdown("# AI Face Swap Tool")
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("""
+            <div class="disclaimer">
+                <h3>⚠️ Ethical Usage Guidelines</h3>
+                <p>This tool is provided for educational and creative purposes only. Please use responsibly:</p>
+                <ul>
+                    <li>Do not use to create misleading or deceptive content</li>
+                    <li>Do not use for harassment or to misrepresent individuals</li>
+                    <li>Always get consent when using someone's likeness</li>
+                    <li>Be aware that creating deepfakes may violate laws in some jurisdictions</li>
+                </ul>
+            </div>
+            """)
+            
+            gr.Markdown("""
+            <div class="instructions">
+                <h3>📝 How to Use This Tool</h3>
+                <ol>
+                    <li><b>Source Image:</b> Upload a clear photo of the face you want to use</li>
+                    <li><b>Target Image:</b> Upload the photo where you want to place the face</li>
+                    <li><b>Face Enhancer:</b> Toggle this option to improve the quality of the swapped face</li>
+                    <li>Click the "Swap Face" button and wait for processing to complete</li>
+                </ol>
+                <p><b>Tips for best results:</b></p>
+                <ul>
+                    <li>Use high-resolution images with clear, front-facing faces</li>
+                    <li>Ensure good lighting in both photos</li>
+                    <li>Similar face angles work best</li>
+                    <li>Processing may take 10-30 seconds depending on image size</li>
+                </ul>
+            </div>
+            """)
+    
+    with gr.Row():
+        with gr.Column():
+            source_image = gr.Image(label="Source Face", info="Upload a photo with the face you want to use")
+        with gr.Column():
+            target_image = gr.Image(label="Target Image", info="Upload the photo where you want to place the face")
+    
+    with gr.Row():
+        face_enhancer = gr.Checkbox(
+            label="Apply Face Enhancement", 
+            info="Enable this to improve the quality and realism of the result",
+            value=True
+        )
+    
+    with gr.Row():
+        swap_button = gr.Button("Swap Face", variant="primary")
+    
+    output_image = gr.Image(label="Result")
+    
+    swap_button.click(
+        fn=swap_face,
+        inputs=[source_image, target_image, face_enhancer],
+        outputs=output_image
+    )
+    
+    gr.Markdown("""
+    ### How It Works
+    This application uses AI to detect faces in both images, then carefully transplants the face from 
+    the source image onto the target image while preserving natural appearance. The optional face 
+    enhancement feature uses additional AI processing to improve skin texture and details.
+    """)
+
+# Launch the application
 app.launch()