init commit

---
title: InSPyReNet Background Remover
emoji: 🖼️
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit
---

# InSPyReNet Background Remover

This Space uses InSPyReNet for high-quality background removal and image masking.

## Features

- **Transparent Background (RGBA)**: Remove background and get PNG with transparency
- **Green Background**: Replace background with green screen
- **White Background**: Replace background with white color
- **Blur Background**: Keep background but blur it
- **Mask Only**: Get the raw saliency mask (grayscale)
- **Overlay**: Highlight detected object with edges

## Credits

- [InSPyReNet](https://github.com/plemeri/InSPyReNet) - ACCV 2022
- [transparent-background](https://github.com/plemeri/transparent-background) - Python package

README.md

@@ -1,14 +1,29 @@
----
-title: Inspyrenet Background Remove
-emoji: 🐨
-colorFrom: indigo
-colorTo: yellow
-sdk: gradio
-sdk_version: 6.2.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: Using Inspyrenet to remove backgrounds
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: InSPyReNet Background Remover
+emoji: 🖼️
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# InSPyReNet Background Remover
+
+This Space uses InSPyReNet for high-quality background removal and image masking.
+
+## Features
+
+- **Transparent Background (RGBA)**: Remove background and get PNG with transparency
+- **Green Background**: Replace background with green screen
+- **White Background**: Replace background with white color
+- **Blur Background**: Keep background but blur it
+- **Mask Only**: Get the raw saliency mask (grayscale)
+- **Overlay**: Highlight detected object with edges
+
+## Credits
+
+- [InSPyReNet](https://github.com/plemeri/InSPyReNet) - ACCV 2022
+- [transparent-background](https://github.com/plemeri/transparent-background) - Python package

app.py

@@ -0,0 +1,108 @@
+import spaces
+import gradio as gr
+from PIL import Image
+from transparent_background import Remover
+import numpy as np
+
+# Initialize the model globally
+remover = Remover(jit=False)
+
+@spaces.GPU
+def process_image(input_image, output_type):
+    """
+    Process image with different output types:
+    - Transparent Background (RGBA): Shows masked image with transparent background
+    - Green Background: Shows masked image with green screen
+    - White Background: Shows masked image with white background
+    - Blur Background: Shows image with blurred background
+    - Mask Only: Shows the grayscale saliency mask
+    - Overlay: Shows object highlighted with edges on original image
+    """
+    global remover
+    
+    if input_image is None:
+        return None
+    
+    if output_type == "Transparent Background (RGBA)":
+        # Returns the masked image with transparent background
+        output = remover.process(input_image, type='rgba')
+        
+    elif output_type == "Green Background":
+        # Returns the masked image with green screen background
+        output = remover.process(input_image, type='green')
+        
+    elif output_type == "White Background":
+        # Returns the masked image with white background
+        output = remover.process(input_image, type='white')
+        
+    elif output_type == "Blur Background":
+        # Returns the image with blurred background
+        output = remover.process(input_image, type='blur')
+        
+    elif output_type == "Mask Only":
+        # Returns only the grayscale saliency mask
+        output = remover.process(input_image, type='map')
+        # Convert to grayscale if needed
+        if isinstance(output, Image.Image):
+            output = output.convert('L')
+        else:
+            output = Image.fromarray((output * 255).astype(np.uint8), mode='L')
+            
+    elif output_type == "Overlay":
+        # Returns image with salient object highlighted
+        output = remover.process(input_image, type='overlay')
+        
+    else:
+        # Default: Transparent background
+        output = remover.process(input_image, type='rgba')
+    
+    return output
+
+# Description with links
+description = """
+<h1 align="center">InSPyReNet Background Remover</h1>
+<p align="center">
+    <a href="https://github.com/plemeri/InSPyReNet" target="_blank">[GitHub - InSPyReNet]</a>
+    <a href="https://github.com/plemeri/transparent-background" target="_blank">[GitHub - transparent-background]</a>
+</p>
+<p align="center">
+    Powered by InSPyReNet (ACCV 2022) - High Resolution Salient Object Detection
+</p>
+"""
+
+# Output type choices with descriptions
+output_choices = [
+    "Transparent Background (RGBA)",  # Actual masked image with transparency
+    "Green Background",               # Masked image on green screen
+    "White Background",               # Masked image on white
+    "Blur Background",                # Original with blurred background
+    "Mask Only",                      # Just the saliency mask
+    "Overlay"                         # Highlighted edges on original
+]
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=process_image,
+    inputs=[
+        gr.Image(type="pil", label="Input Image", height=512),
+        gr.Radio(
+            choices=output_choices,
+            label="Output Type",
+            value="Transparent Background (RGBA)",
+            info="Select how you want the masked image displayed"
+        )
+    ],
+    outputs=gr.Image(type="pil", label="Output Image", height=512),
+    description=description,
+    theme='bethecloud/storj_theme',
+    examples=[
+        ["1.png", "Transparent Background (RGBA)"],
+        ["1.png", "Green Background"],
+        ["2.png", "White Background"],
+        ["2.png", "Mask Only"],
+    ],
+    cache_examples=False  # Set to True after adding example images
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1,6 @@
+gradio
+transparent-background
+numpy
+Pillow
+torch
+torchvision