Update app.py

app.py

@@ -7,13 +7,13 @@ from torchvision import transforms
 import uuid
 import os
 
-# Device selection
+# Select device
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print(f"Using device: {device}")
 
 torch.set_float32_matmul_precision(["high", "highest"][0])
 
-# Load model
+# Load BiRefNet model
 birefnet = AutoModelForImageSegmentation.from_pretrained(
     "ZhengPeng7/BiRefNet", trust_remote_code=True
 )
@@ -40,60 +40,24 @@ def process(image):
     image.putalpha(mask)
     return image
 
-# Image Upload tab
+# Main function: image upload → preview + downloadable PNG
 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
-
-# File tab
-def process_file(f):
-    name_path = f.rsplit(".", 1)[0] + ".png"
-    im = load_img(f, output_type="pil").convert("RGB")
-    transparent = process(im)
-    transparent.save(name_path)
-    return name_path
 
-# Example image
-url_example = "https://hips.hearstapps.com/hmg-prod/images/gettyimages-1229892983-square.jpg"
-chameleon = load_img(url_example, output_type="pil")
+    return processed_image, filename
 
-# Tab 1: Upload + Preview + Download
-tab1 = gr.Interface(
+# Gradio interface
+demo = gr.Interface(
     fn,
     inputs=gr.Image(label="Upload an image"),
     outputs=[
-        gr.Image(label="Preview"),
-        gr.File(label="Download Processed Image")
+        gr.Image(label="Processed Preview"),
+        gr.File(label="Download PNG")
     ],
-    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"
-)
-
-# Final App
-demo = gr.TabbedInterface(
-    [tab1, tab2, tab3],
-    ["Image Upload", "URL Input", "File Output"],
     title="Background Removal Tool"
 )