Update app.py

app.py

@@ -7,19 +7,19 @@ from torchvision import transforms
 import uuid
 import os
 
-# Automatically select device (GPU or CPU)
+# Device selection
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print(f"Using device: {device}")
 
 torch.set_float32_matmul_precision(["high", "highest"][0])
 
-# Load the segmentation model
+# Load model
 birefnet = AutoModelForImageSegmentation.from_pretrained(
     "ZhengPeng7/BiRefNet", trust_remote_code=True
 )
 birefnet.to(device)
 
-# Image preprocessing
+# Preprocessing
 transform_image = transforms.Compose(
     [
         transforms.Resize((1024, 1024)),
@@ -40,17 +40,15 @@ def process(image):
     image.putalpha(mask)
     return image
 
-# Main function: returns both a preview and a downloadable file
+# Image Upload tab
 def fn(image):
     im = load_img(image, output_type="pil").convert("RGB")
     processed_image = process(im)
-
     filename = f"/tmp/processed_{uuid.uuid4().hex}.png"
     processed_image.save(filename)
+    return processed_image, filename
 
-    return processed_image, filename  # Preview + downloadable image
-
-# File-only processing tab
+# File tab
 def process_file(f):
     name_path = f.rsplit(".", 1)[0] + ".png"
     im = load_img(f, output_type="pil").convert("RGB")
@@ -58,26 +56,45 @@ def process_file(f):
     transparent.save(name_path)
     return name_path
 
-# Components
-preview_image = gr.Image(label="Preview")
-download_file = gr.File(label="Download Processed Image")
-image_upload = gr.Image(label="Upload an image")
-image_file_upload = gr.Image(label="Upload an image", type="filepath")
-url_input = gr.Textbox(label="Paste an image URL")
-output_file = gr.File(label="Output PNG File")
-
-# Example image (from URL instead of invalid local path)
+# Example image
 url_example = "https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"
 chameleon = load_img(url_example, output_type="pil")
 
-# Interface Tabs
-tab1 = gr.Interface(fn, inputs=image_upload, outputs=[preview_image, download_file], examples=[chameleon], api_name="image")
-tab2 = gr.Interface(fn, inputs=url_input, outputs=preview_image, examples=[url_example], api_name="text")
-tab3 = gr.Interface(process_file, inputs=image_file_upload, outputs=output_file, examples=[], api_name="png")
+# Tab 1: Upload + Preview + Download
+tab1 = gr.Interface(
+    fn,
+    inputs=gr.Image(label="Upload an image"),
+    outputs=[
+        gr.Image(label="Preview"),
+        gr.File(label="Download Processed Image")
+    ],
+    examples=[chameleon],
+    api_name="image"
+)
+
+# Tab 2: URL input + Preview
+tab2 = gr.Interface(
+    fn,
+    inputs=gr.Textbox(label="Paste an image URL"),
+    outputs=gr.Image(label="Preview"),
+    examples=[url_example],
+    api_name="text"
+)
+
+# Tab 3: File path input + downloadable result
+tab3 = gr.Interface(
+    process_file,
+    inputs=gr.Image(label="Upload an image", type="filepath"),
+    outputs=gr.File(label="Output PNG File"),
+    examples=[],
+    api_name="png"
+)
 
-# Combine tabs into one app
+# Final App
 demo = gr.TabbedInterface(
-    [tab1, tab2, tab3], ["Image Upload", "URL Input", "File Output"], title="Background Removal Tool"
+    [tab1, tab2, tab3],
+    ["Image Upload", "URL Input", "File Output"],
+    title="Background Removal Tool"
 )
 
 if __name__ == "__main__":