Update app.py

app.py

@@ -40,21 +40,15 @@ def download_file(url, dir_path, file_name):
             print("Download complete.")
         except Exception as e:
             print(f"Error downloading {file_name}: {e}")
-            # In case wget is not available, you might need to use requests or urllib
-            # import requests
-            # with open(file_path, 'wb') as f:
-            #     f.write(requests.get(url).content)
     return file_path
 
 # --- DOWNLOAD MODELS AND EXAMPLES ---
 print("Checking for required files...")
-# Models
 models_dir = 'models'
 download_file('https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth', models_dir, 'realesr-general-x4v3.pth')
 download_file('https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth', models_dir, 'GFPGANv1.4.pth')
 download_file('https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth', models_dir, 'RestoreFormer.pth')
 
-# Example Images
 examples_dir = 'examples'
 example1_path = download_file('https://raw.githubusercontent.com/TencentARC/GFPGAN/master/inputs/whole_imgs/10045.png', examples_dir, 'example1.png')
 example2_path = download_file('https://raw.githubusercontent.com/TencentARC/GFPGAN/master/inputs/whole_imgs/Blake_Lively.jpg', examples_dir, 'example2.jpg')
@@ -70,13 +64,13 @@ try:
     model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
     half = torch.cuda.is_available()
     bg_upsampler = RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=half)
-    print("Background Upsampler (Real-ESRGAN) loaded.")
+    print("Background Upsampler (Real-ESRGAN) loaded for 4x enhancement.")
 except Exception as e:
     print(f"Error loading background upsampler: {e}. The app may not work correctly.")
 
 # --- CORE IMAGE PROCESSING FUNCTION ---
-def upscale_image(img_path, version, scale):
-    """Enhance an image using GFPGAN and Real-ESRGAN."""
+def upscale_image(img_path, version):
+    """Enhance an image using GFPGAN and Real-ESRGAN with a fixed 4x upscale."""
     if not img_path:
         raise gr.Error("Please upload an image.")
     if not bg_upsampler:
@@ -90,22 +84,15 @@ def upscale_image(img_path, version, scale):
 
         face_enhancer = GFPGANer(
             model_path=os.path.join(models_dir, f'{version}.pth'),
-            upscale=2, # GFPGAN native upscale factor
+            upscale=2, # Native GFPGAN upscale factor
             arch='RestoreFormer' if version == 'RestoreFormer' else 'clean',
             channel_multiplier=2,
-            bg_upsampler=bg_upsampler
+            bg_upsampler=bg_upsampler # Real-ESRGAN used for 4x background
         )
         
+        # This will produce a 4x enhanced image because the bg_upsampler is 4x
         _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
 
-        if scale != 2:
-            h, w = output.shape[0:2]
-            target_w, target_h = int(w * scale / 2), int(h * scale / 2)
-            if target_w > 8000 or target_h > 8000:
-                raise gr.Error(f"Target size is too large. Please choose a smaller scale.")
-            interpolation = cv2.INTER_LANCZOS4 if scale > 2 else cv2.INTER_AREA
-            output = cv2.resize(output, (target_w, target_h), interpolation=interpolation)
-
         output_rgb = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
         ext = 'png' if has_alpha else 'jpg'
         
@@ -121,7 +108,7 @@ def upscale_image(img_path, version, scale):
 # --- GRADIO UI LAYOUT ---
 with gr.Blocks(css=CSS_STYLING, theme=gr.themes.Base()) as demo:
     gr.Markdown("<h1 id='main-title'>NeuraVision AI Image Upscaler</h1>", elem_id="main-title")
-    gr.Markdown("<p id='main-subtitle'>Enhance old, blurry, and low-resolution photos with AI.</p>", elem_id="main-subtitle")
+    gr.Markdown("<p id='main-subtitle'>Enhance old, blurry, and low-resolution photos with AI (Fixed 4x Upscale).</p>", elem_id="main-subtitle")
 
     with gr.Row(variant="panel"):
         # LEFT COLUMN (INPUT & CONTROLS)
@@ -130,19 +117,14 @@ with gr.Blocks(css=CSS_STYLING, theme=gr.themes.Base()) as demo:
             
             version = gr.Radio(
                 ['GFPGANv1.4', 'RestoreFormer'], value='GFPGANv1.4', 
-                label='AI Model', info="v1.4 is best for general use. RestoreFormer for very old photos."
-            )
-            
-            scale = gr.Slider(
-                minimum=1, maximum=8, step=0.5, value=4, 
-                label="Upscale Factor", info="How many times larger to make the image."
+                label='AI Model', info="v1.4 for general use. RestoreFormer for old photos."
             )
             
             submit_btn = gr.Button("Enhance Image", variant="primary", elem_id="submit-button")
             
             gr.Examples(
-                examples=[[example1_path, "RestoreFormer", 4], [example2_path, "GFPGANv1.4", 4]],
-                inputs=[input_image, version, scale],
+                examples=[[example1_path, "RestoreFormer"], [example2_path, "GFPGANv1.4"]],
+                inputs=[input_image, version],
                 label="Click an example to start"
             )
         
@@ -154,7 +136,7 @@ with gr.Blocks(css=CSS_STYLING, theme=gr.themes.Base()) as demo:
     # --- BUTTON & EVENT HANDLING ---
     submit_btn.click(
         fn=upscale_image, 
-        inputs=[input_image, version, scale], 
+        inputs=[input_image, version], 
         outputs=[output_image, download_button]
     )
     input_image.clear(lambda: (None, None), None, [output_image, download_button])