Create app.py

app.py

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+import gradio as gr
+from PIL import Image
+from transparent_background import Remover
+import numpy as np
+
+# Initialize the model globally
+remover = Remover()
+
+def process_image(input_image, torchscript_jit, output_type):
+    global remover
+    if torchscript_jit == "on" and not isinstance(remover, Remover(jit=True).__class__):
+        remover = Remover(jit=True)
+    elif torchscript_jit == "default" and not isinstance(remover, Remover().__class__):
+        remover = Remover()
+    
+    if output_type == "Mask only":
+        # Process the image and get only the mask
+        output = remover.process(input_image, type='map')
+        # Convert the mask to a black and white image
+        mask = Image.fromarray((output * 255).astype(np.uint8))
+        return mask
+    else:
+        # Process the image and return the RGBA result
+        output = remover.process(input_image, type='rgba')
+        return output
+
+iface = gr.Interface(
+    fn=process_image,
+    inputs=[
+        gr.Image(type="pil", label="Input Image"),
+        gr.Radio(["default", "on"], label="TorchScript JIT", value="default"),
+        gr.Radio(["Default", "Mask only"], label="Output Type", value="Default")
+    ],
+    outputs=gr.Image(type="pil", label="Output Image"),
+    title="Inspyrenet Background Remover",
+    description="Remove the background from an image using Inspyrenet. Choose 'Mask only' for a black and white mask, or 'Default' for the image with transparent background.",
+    theme='bethecloud/storj_theme',
+)
+
+if __name__ == "__main__":
+    iface.launch()