add Poster references
Browse files- app.py +8 -1
- messis/messis.py +0 -1
- pages/2_Perform_Crop_Classification.py +2 -3
app.py
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@@ -5,11 +5,18 @@ def main():
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st.title("Messis πΎ - Crop Classification π")
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st.write("Welcome to the Messis Crop Classification
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st.page_link("app.py", label="Home", icon="π ")
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st.page_link("pages/1_Select_Location.py", label="Select Location", icon="π")
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st.page_link("pages/2_Perform_Crop_Classification.py", label="Perform Crop Classification", icon="π")
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if __name__ == "__main__":
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main()
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st.title("Messis πΎ - Crop Classification π")
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st.write("Welcome to the Messis Crop Classification demo. Use the sidebar to navigate between selecting the location you are interested in and performing crop classification.")
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st.page_link("app.py", label="Home", icon="π ")
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st.page_link("pages/1_Select_Location.py", label="Select Location", icon="π")
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st.page_link("pages/2_Perform_Crop_Classification.py", label="Perform Crop Classification", icon="π")
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st.markdown("""
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---
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### Ausstellung Bachelor-Diplomarbeiten
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""")
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st.page_link("https://docs.google.com/document/d/1pd_rAwvHLSp1ba_JUFa6wfdbPoU93l41u1OZl_40Noo/edit?usp=sharing", label="Referenzen Poster", icon="π")
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if __name__ == "__main__":
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main()
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messis/messis.py
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@@ -14,7 +14,6 @@ import json
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from messis.prithvi import TemporalViTEncoder, ConvTransformerTokensToEmbeddingNeck, ConvTransformerTokensToEmbeddingBottleneckNeck
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def safe_shape(x):
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if isinstance(x, tuple):
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# loop through tuple
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from messis.prithvi import TemporalViTEncoder, ConvTransformerTokensToEmbeddingNeck, ConvTransformerTokensToEmbeddingBottleneckNeck
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def safe_shape(x):
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if isinstance(x, tuple):
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# loop through tuple
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pages/2_Perform_Crop_Classification.py
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@@ -69,7 +69,7 @@ def perform_inference_step():
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m = leafmap.Map(center=(lat, lon), zoom=10, draw_control=False)
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# Perform inference
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if st.
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predictions = perform_inference(lon, lat, model, config, debug=True)
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m.add_data(predictions,
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@@ -86,8 +86,7 @@ def perform_inference_step():
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url=presigned_url,
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name="Sentinel-2 Satellite Imagery",
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bands=selected_bands,
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rescale=f"{vmin_vmax[selected_band][0]},{vmin_vmax[selected_band][1]}"
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zoom_to_layer=True
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)
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# Show the POI on the map
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m = leafmap.Map(center=(lat, lon), zoom=10, draw_control=False)
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# Perform inference
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if st.button("Perform Crop Classification", type="primary"):
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predictions = perform_inference(lon, lat, model, config, debug=True)
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m.add_data(predictions,
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url=presigned_url,
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name="Sentinel-2 Satellite Imagery",
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bands=selected_bands,
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rescale=f"{vmin_vmax[selected_band][0]},{vmin_vmax[selected_band][1]}"
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)
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# Show the POI on the map
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