Update app.py

app.py

@@ -14,6 +14,17 @@ import cv2
 import insightface
 import numpy as np
 import gradio.components as gr_comp
+import asyncio
+import logging
+from PIL import Image
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+
+# Constants for DPI and pixel dimensions
+DPI = 300
+WIDTH_PIXELS = 1182
+HEIGHT_PIXELS = 1773
 
 # Load the insightface model once
 providers = ["CUDAExecutionProvider", "CPUExecutionProvider"] if cv2.cuda.getCudaEnabledDeviceCount() > 0 else ["CPUExecutionProvider"]
@@ -37,23 +48,34 @@ def update_templates(gender):
         return gr.Dropdown.update(choices=[])
 
 # Main function for face swapping
-def face_swap_and_merge(src_image, gender, template_choice):
-    # Resize the source image to 1200x1800 for uniform processing
-    src_image = cv2.resize(src_image, (1200, 1800))
-
-    template_image_path = f'{template_choice}'
-    template_image = cv2.imread(template_image_path, cv2.IMREAD_UNCHANGED)
-
-    # Resize the template image to 1200x1800 for uniform processing
-    template_image = cv2.resize(template_image, (1200, 1800))
-
-    src_faces = FACE_ANALYSER.get(src_image)
-    template_faces = FACE_ANALYSER.get(template_image)
-
-    img_fake = model_swap_insightface.get(img=template_image, target_face=template_faces[0], source_face=src_faces[0], paste_back=True)
-    img_fake_rgb = cv2.cvtColor(img_fake, cv2.COLOR_BGR2RGB)
-
-    return img_fake_rgb
+async def face_swap_and_merge(src_image, gender, template_choice):
+    try:
+        logging.info("Starting face swap and merge process")
+        
+        # Resize the source image to the required dimensions for uniform processing
+        src_image = cv2.resize(src_image, (WIDTH_PIXELS, HEIGHT_PIXELS))
+
+        template_image_path = f'{template_choice}'
+        template_image = cv2.imread(template_image_path, cv2.IMREAD_UNCHANGED)
+
+        # Resize the template image to the required dimensions for uniform processing
+        template_image = cv2.resize(template_image, (WIDTH_PIXELS, HEIGHT_PIXELS))
+
+        src_faces = FACE_ANALYSER.get(src_image)
+        template_faces = FACE_ANALYSER.get(template_image)
+
+        img_fake = model_swap_insightface.get(img=template_image, target_face=template_faces[0], source_face=src_faces[0], paste_back=True)
+        img_fake_rgb = cv2.cvtColor(img_fake, cv2.COLOR_BGR2RGB)
+
+        # Convert to PIL image to set DPI
+        pil_image = Image.fromarray(img_fake_rgb)
+        pil_image.info['dpi'] = (DPI, DPI)
+        
+        logging.info("Face swap and merge process completed successfully")
+        return np.array(pil_image)
+    except Exception as e:
+        logging.error(f"Error in face_swap_and_merge: {e}")
+        return None
 
 # Function to clear only the output image
 def clear_output():
@@ -67,23 +89,23 @@ def clear_all():
 with gr.Blocks(theme='upsatwal/mlsc_tiet') as iface:
     gr.Markdown("# Face Changer")
     gr.Markdown(" ")
-    
+
     src_image = gr.Image(type="numpy", label="Input Image")
     gender = gr.Dropdown(["Male", "Female"], label="Select Gender", interactive=True)
     template_choice = gr.Dropdown([], label="Select Template", interactive=True)
-    
+
     gender.change(fn=update_templates, inputs=gender, outputs=template_choice)
-    
+
     result_image = gr.Image(label="Output Image")
-    
+
     submit_button = gr.Button("Submit")
     submit_button.click(fn=face_swap_and_merge, inputs=[src_image, gender, template_choice], outputs=result_image)
 
     clear_output_button = gr.Button("Clear Output")
     clear_output_button.click(fn=clear_output, inputs=[], outputs=result_image)
-    
+
     clear_all_button = gr.Button("Clear All")
     clear_all_button.click(fn=clear_all, inputs=[], outputs=[src_image, gender, template_choice, result_image])
-    
+
     iface.launch(debug=True)