Update app.py

app.py

@@ -15,29 +15,28 @@ img_mode = "RGBA"
 
 @spaces.GPU
 def realesrgan(img, model_name, denoise_strength, face_enhance, outscale):
-    """Real-ESRGAN function to restore (and upscale) images.
-    """
+    """Real-ESRGAN function to restore (and upscale) images."""
     if not img:
         return
 
     # Define model parameters
-    if model_name == 'RealESRGAN_x4plus':  # x4 RRDBNet model
+    if model_name == 'RealESRGAN_x4plus':
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
         netscale = 4
         file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth']
-    elif model_name == 'RealESRNet_x4plus':  # x4 RRDBNet model
+    elif model_name == 'RealESRNet_x4plus':
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
         netscale = 4
         file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth']
-    elif model_name == 'RealESRGAN_x4plus_anime_6B':  # x4 RRDBNet model with 6 blocks
+    elif model_name == 'RealESRGAN_x4plus_anime_6B':
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
         netscale = 4
         file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth']
-    elif model_name == 'RealESRGAN_x2plus':  # x2 RRDBNet model
+    elif model_name == 'RealESRGAN_x2plus':
         model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
         netscale = 2
         file_url = ['https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth']
-    elif model_name == 'realesr-general-x4v3':  # x4 VGG-style model (S size)
+    elif model_name == 'realesr-general-x4v3':
         model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
         netscale = 4
         file_url = [
@@ -45,23 +44,19 @@ def realesrgan(img, model_name, denoise_strength, face_enhance, outscale):
             'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth'
         ]
 
-    # Determine model paths
     model_path = os.path.join('weights', model_name + '.pth')
     if not os.path.isfile(model_path):
         ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
         for url in file_url:
-            # model_path will be updated
             model_path = load_file_from_url(
                 url=url, model_dir=os.path.join(ROOT_DIR, 'weights'), progress=True, file_name=None)
 
-    # Use dni to control the denoise strength
     dni_weight = None
     if model_name == 'realesr-general-x4v3' and denoise_strength != 1:
         wdn_model_path = model_path.replace('realesr-general-x4v3', 'realesr-general-wdn-x4v3')
         model_path = [model_path, wdn_model_path]
         dni_weight = [denoise_strength, 1 - denoise_strength]
 
-    # Restorer Class
     upsampler = RealESRGANer(
         scale=netscale,
         model_path=model_path,
@@ -74,7 +69,6 @@ def realesrgan(img, model_name, denoise_strength, face_enhance, outscale):
         gpu_id=None
     )
 
-    # Use GFPGAN for face enhancement
     if face_enhance:
         from gfpgan import GFPGANer
         face_enhancer = GFPGANer(
@@ -84,11 +78,9 @@ def realesrgan(img, model_name, denoise_strength, face_enhance, outscale):
             channel_multiplier=2,
             bg_upsampler=upsampler)
 
-    # Convert the input PIL image to cv2 image, so that it can be processed by realesrgan
     cv_img = numpy.array(img)
     img = cv2.cvtColor(cv_img, cv2.COLOR_RGBA2BGRA)
 
-    # Apply restoration
     try:
         if face_enhance:
             _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
@@ -98,49 +90,29 @@ def realesrgan(img, model_name, denoise_strength, face_enhance, outscale):
         print('Error', error)
         print('If you encounter CUDA out of memory, try to set --tile with a smaller number.')
     else:
-        # Save restored image and return it to the output Image component
-        if img_mode == 'RGBA':  # RGBA images should be saved in png format
-            extension = 'png'
-        else:
-            extension = 'jpg'
+        extension = 'png' if img_mode == 'RGBA' else 'jpg'
 
         out_filename = f"output_{rnd_string(8)}.{extension}"
         cv2.imwrite(out_filename, output)
         global last_file
         last_file = out_filename
-        return out_filename
 
+        output_img = cv2.cvtColor(output, cv2.COLOR_BGRA2RGBA) if img_mode == "RGBA" else output
+        return out_filename, image_properties(output_img)
 
 def rnd_string(x):
-    """Returns a string of 'x' random characters
-    """
     characters = "abcdefghijklmnopqrstuvwxyz_0123456789"
-    result = "".join((random.choice(characters)) for i in range(x))
-    return result
-
+    return "".join((random.choice(characters)) for i in range(x))
 
 def reset():
-    """Resets the Image components of the Gradio interface and deletes
-    the last processed image
-    """
     global last_file
     if last_file:
         print(f"Deleting {last_file} ...")
         os.remove(last_file)
         last_file = None
-    return gr.update(value=None), gr.update(value=None)
-
+    return gr.update(value=None), gr.update(value=None), gr.update(value=None)
 
 def has_transparency(img):
-    """This function works by first checking to see if a "transparency" property is defined
-    in the image's info -- if so, we return "True". Then, if the image is using indexed colors
-    (such as in GIFs), it gets the index of the transparent color in the palette
-    (img.info.get("transparency", -1)) and checks if it's used anywhere in the canvas
-    (img.getcolors()). If the image is in RGBA mode, then presumably it has transparency in
-    it, but it double-checks by getting the minimum and maximum values of every color channel
-    (img.getextrema()), and checks if the alpha channel's smallest value falls below 255.
-    https://stackoverflow.com/questions/43864101/python-pil-check-if-image-is-transparent
-    """
     if img.info.get("transparency", None) is not None:
         return True
     if img.mode == "P":
@@ -154,69 +126,70 @@ def has_transparency(img):
             return True
     return False
 
-
 def image_properties(img):
     """Returns the dimensions (width and height) and color mode of the input image and
     also sets the global img_mode variable to be used by the realesrgan function
     """
     global img_mode
-    if img:
+    if img is None:  # Explicitly check for None
+        return "No image data available."
+
+    if isinstance(img, numpy.ndarray):  # Handle NumPy array case
+        height, width = img.shape[:2]
+        channels = img.shape[2] if len(img.shape) > 2 else 1
+        img_mode = "RGBA" if channels == 4 else "RGB" if channels == 3 else "Grayscale"
+        return f"Resolution: Width: {width}, Height: {height}  |  Color Mode: {img_mode}"
+    
+    if hasattr(img, "info") and hasattr(img, "mode") and hasattr(img, "size"):  # Handle PIL images
         if has_transparency(img):
             img_mode = "RGBA"
         else:
             img_mode = "RGB"
-        properties = f"Resolution: Width: {img.size[0]}, Height: {img.size[1]}  |  Color Mode: {img_mode}"
-        return properties
-
+        return f"Resolution: Width: {img.size[0]}, Height: {img.size[1]}  |  Color Mode: {img_mode}"
+    
+    return "Unsupported image format."
 
 def main():
-    # Gradio Interface
     with gr.Blocks(theme=gr.themes.Default(primary_hue="pink", secondary_hue="rose"), title="Ilaria Upscaler 💖") as app:
 
         gr.Markdown(
             """# <div align="center"> Ilaria Upscaler 💖 </div>  
         """
         )
-
         with gr.Accordion("Upscaling option"):
             with gr.Row():
-                model_name = gr.Dropdown(label="Upscaler model",
-                                         choices=["RealESRGAN_x4plus", "RealESRNet_x4plus", "RealESRGAN_x4plus_anime_6B",
-                                                  "RealESRGAN_x2plus", "realesr-general-x4v3"],
-                                         value="RealESRGAN_x4plus_anime_6B", show_label=True)
-                denoise_strength = gr.Slider(label="Denoise Strength",
-                                             minimum=0, maximum=1, step=0.1, value=0.5)
-                outscale = gr.Slider(label="Resolution upscale",
-                                     minimum=1, maximum=6, step=1, value=4, show_label=True)
-                face_enhance = gr.Checkbox(label="Face Enhancement (GFPGAN)",
-                )
-                
+                model_name = gr.Dropdown(label="Model", 
+                                        choices=["RealESRGAN_x4plus", "RealESRNet_x4plus", "RealESRGAN_x4plus_anime_6B", "RealESRGAN_x2plus", "realesr-general-x4v3"], 
+                                        value="RealESRGAN_x4plus")
+                denoise_strength = gr.Slider(label="Denoise Strength", minimum=0, maximum=1, step=0.1, value=0.5)
+                outscale = gr.Slider(label="Resolution Upscale", minimum=1, maximum=6, step=1, value=4)
+                face_enhance = gr.Checkbox(label="Face Enhancement")
+
         with gr.Row():
             with gr.Group():
-                input_image = gr.Image(label="Input Image", type="pil", image_mode="RGBA")
-                input_image_properties = gr.Textbox(label="Image Properties", max_lines=1)
-            output_image = gr.Image(label="Output Image", image_mode="RGBA")
+                input_image = gr.Image(label="Input Image", type="pil")
+                input_properties = gr.Textbox(label="Input Image Properties", interactive=False)
+
+            with gr.Group():
+                output_image = gr.Image(label="Output Image")
+                output_properties = gr.Textbox(label="Output Image Properties", interactive=False)
+
         with gr.Row():
-            reset_btn = gr.Button("Remove images")
-            restore_btn = gr.Button("Upscale")
-
-        # Event listeners:
-        input_image.change(fn=image_properties, inputs=input_image, outputs=input_image_properties)
-        restore_btn.click(fn=realesrgan,
-                          inputs=[input_image, model_name, denoise_strength, face_enhance, outscale],
-                          outputs=output_image)
-        reset_btn.click(fn=reset, inputs=[], outputs=[output_image, input_image])
-        # reset_btn.click(None, inputs=[], outputs=[input_image], _js="() => (null)\n")
-        # Undocumented method to clear a component's value using Javascript
+            reset_btn = gr.Button("Reset")
+            upscale_btn = gr.Button("Upscale")
+
+        input_image.change(fn=image_properties, inputs=input_image, outputs=input_properties)
+        upscale_btn.click(fn=realesrgan, 
+                        inputs=[input_image, model_name, denoise_strength, face_enhance, outscale], 
+                        outputs=[output_image, output_properties])
+        reset_btn.click(fn=reset, inputs=[], outputs=[input_image, output_image, input_properties])
 
         gr.Markdown(
             """Made with love by Ilaria 💖 | Support me on [Ko-Fi](https://ko-fi.com/ilariaowo) | Using [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN).
-
         """
         )
 
     app.launch()
 
-
 if __name__ == "__main__":
-    main()
+    main()