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SatelliteClassification.py
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@@ -261,7 +261,7 @@ def create_interface():
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fn=predict_images,
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inputs=[],
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outputs=[
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gr.Image(type="pil", label="Classification Results (
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gr.Textbox(label="Summary", lines=3)
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],
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title="🛰️ Satellite Image Classification with ResNet18",
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@@ -269,7 +269,7 @@ def create_interface():
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This app classifies satellite images from the EuroSAT dataset using a trained ResNet18 model.
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**How it works:**
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- Loads
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- Each image has 13 spectral bands, converted to RGB for display
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- Shows true labels vs predicted labels
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- Green titles = correct predictions, Red titles = incorrect predictions
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@@ -277,7 +277,7 @@ def create_interface():
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**Dataset:** EuroSAT with 13 multispectral bands
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**Model:** ResNet18 with dropout, trained on 13-channel input
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Click "Generate" to process
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""",
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examples=[],
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cache_examples=False,
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fn=predict_images,
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inputs=[],
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outputs=[
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gr.Image(type="pil", label="Classification Results (10 Random Images)"),
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gr.Textbox(label="Summary", lines=3)
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],
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title="🛰️ Satellite Image Classification with ResNet18",
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This app classifies satellite images from the EuroSAT dataset using a trained ResNet18 model.
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**How it works:**
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- Loads 10 random satellite images from the test set
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- Each image has 13 spectral bands, converted to RGB for display
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- Shows true labels vs predicted labels
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- Green titles = correct predictions, Red titles = incorrect predictions
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**Dataset:** EuroSAT with 13 multispectral bands
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**Model:** ResNet18 with dropout, trained on 13-channel input
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Click "Generate" to process 10 new random images!
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""",
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examples=[],
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cache_examples=False,
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