Added Three files

Uplaoded SGDNet Model, app.py and Requirements.txt

README.md

@@ -1,3 +1,13 @@
----
-license: mit
----
+# SGDNet Gradio Interface
+
+This is a Gradio interface for the SGDNet model, which extracts glacier boundaries from multisource remote sensing data.
+
+## Setup
+
+1. Install the required packages:
+pip install -r requirements.txt
+
+2. Run the Gradio app:
+python gradio_app.py
+
+3. Open your browser to the provided local URL to interact with the interface.

SGDNet.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8db3ec659258f0998d97ad2fa550ba6325b2476b378ff57e0c5c040041fb5235
+size 143376

gradio_app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from pyrsgis import raster, convert
+from sklearn.preprocessing import StandardScaler
+from PIL import Image
+import io
+
+# Load the model
+model = tf.keras.models.load_model('SGDNet.h5')
+
+def predict(image_path):
+    # Process the image file
+    ds, image_data = raster.read(image_path, bands='all')
+    image_data = convert.array_to_table(image_data)
+    scaler = StandardScaler()
+    image_data = scaler.fit_transform(image_data)
+    image_data = image_data.reshape((image_data.shape[0], 1, image_data.shape[1]))
+    
+    # Make prediction
+    predicted = model.predict(image_data)
+    predicted_prob = predicted[:, 1]
+    predicted_prob = np.reshape(predicted_prob, (ds.RasterYSize, ds.RasterXSize))
+    
+    # Convert prediction to image
+    im = Image.fromarray((predicted_prob * 255).astype(np.uint8))
+    bio = io.BytesIO()
+    im.save(bio, format='PNG')
+    return bio.getvalue()
+
+def save_uploaded_file(uploaded_file):
+    with open(uploaded_file.name, "wb") as f:
+        f.write(uploaded_file.getbuffer())
+    return uploaded_file.name
+
+with gr.Blocks() as app:
+    with gr.Row():
+        with gr.Column():
+            file_input = gr.File(label="Upload your satellite image")
+            submit_button = gr.Button("Predict")
+        with gr.Column():
+            image_output = gr.Image(label="Predicted Glacier Boundaries")
+
+    submit_button.click(
+        fn=lambda x: predict(save_uploaded_file(x)),
+        inputs=file_input,
+        outputs=image_output
+    )
+
+if __name__ == "__main__":
+    app.launch()
+

requirements.txt

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+numpy
+tensorflow
+pyrsgis
+scikit-learn
+matplotlib
+pandas
+