Update app.py

app.py

@@ -1,144 +1,145 @@
-import itertools
-from datetime import datetime
-from pathlib import Path
-
-import folium
-import streamlit as st
-from loguru import logger as log
-from matplotlib import colors
-from streamlit_folium import st_folium
-
-from utils.folium import (
-    draw_gdf,
-    get_clean_rendering_container,
-    get_map_crop,
-    get_parquet,
-)
-
-COLOR_MAP = {
-    "Grassland": "lime",
-    "Cereals": "saddlebrown",
-    "Other": "white",
-    "Flowers": "cyan",
-    "Vegetables": "purple",
-    "Fruit trees": "darkgreen",
-}
-
-
-id_class = {(i + 1): k for i, k in enumerate(COLOR_MAP.keys())}
-color_map_hex = {k: colors.to_hex(v) for k, v in COLOR_MAP.items()}
-id_map_hex = {(i + 1): v for i, v in enumerate(color_map_hex.values())}
-color_map_hex_r = {v: k for k, v in color_map_hex.items()}
-merged_list = list(itertools.chain(*list(color_map_hex_r.items())))
-
-
-def style_call(feat):
-    di = {
-        "fillColor": id_map_hex[feat["properties"]["class"]],
-        "fillOpacity": 0.7,
-        "color": id_map_hex[feat["properties"]["class"]],
-        "border-width": "thin",
-        "border-color": "#ffffff",
-        "weight": 1.2,
-    }
-    return di
-
-
-# Page configs
-st.set_page_config(page_title="AIDA", page_icon="🌐", layout="wide")
-
-# base paths
-base_path = Path("data")
-inference_path = base_path / "inference"
-
-# list examples and predictions
-inference_paths = sorted(list(inference_path.iterdir()))
-
-example_names = [p.stem for p in inference_paths]
-inference_dict = {p.stem: p for p in inference_paths}
-
-
-def change_key():
-    st.session_state["key_map"] = str(datetime.now())
-
-
-# Create selection menu
-container_predictions = st.container(border=True)
-with container_predictions:
-    col1, col2, col3 = st.columns([0.2, 0.1, 0.7])
-    with col1:
-        prediction_selectbox = st.selectbox(
-            "Select an example",
-            options=example_names,
-            index=None,
-            key="selectbox_pred",
-        )
-    is_prediction_selected = prediction_selectbox is not None
-    if is_prediction_selected:
-        try:
-            # add loading of the selected parquet prediction
-            chosen_tile_path = inference_dict[prediction_selectbox]
-            with open(chosen_tile_path, "rb") as f:
-                prediction_file = f.read()
-        except:
-            st.warning("File not found")
-            chosen_tile_path = None
-            prediction_file = None
-    else:
-        prediction_file = None
-        chosen_tile_path = None
-    with col2:
-        height_value = st.radio(
-            "Map height",
-            options=[800, 500],
-            horizontal=True,
-            key="height_map",
-            on_change=change_key,
-        )
-    with col3:
-        with st.container():
-            st.write("######")
-            with st.expander("See information about the methodology"):
-                st.write(
-                    """The model uses a modified UTAE architecture, a U-Net variant with attention, 
-                    for segmenting crop types from satellite imagery. 
-                    It was trained using Sentinel-2 time series data from several European countries, 
-                    labeled with aggregated Eurocrops data to identify 6 broad crop classes.
-                    More informations about the methodology [HERE](https://huggingface.co/links-ads/aida-cropland-models)"""
-                )
-
-container = get_clean_rendering_container(prediction_selectbox)
-
-
-# Stange Hack to always update the map height I guess
-
-
-container = get_clean_rendering_container(height_value)
-
-# draw map
-interactive_map = get_map_crop()
-
-if prediction_selectbox is not None:
-    # draw prediction
-    draw_gdf(interactive_map, chosen_tile_path, "Prediction", style_call, id_class)
-
-
-with container.form(key="form1", clear_on_submit=True):
-
-    folium.LayerControl().add_to(interactive_map)
-    output_map = st_folium(
-        interactive_map,
-        width=None,
-        height=height_value,
-        returned_objects=["all_drawings"],
-        key=st.session_state.get("key_map", "key_map"),
-    )
-    submit = st.form_submit_button("Recenter map")
-
-# Update messages
-
-
-for name, path in inference_dict.items():
-    if path not in st.session_state.keys():
-        log.info(f"Loading parquet {name}")
-        st.session_state[path] = get_parquet(path, id_class)
+import itertools
+from datetime import datetime
+from pathlib import Path
+
+import folium
+import streamlit as st
+from loguru import logger as log
+from matplotlib import colors
+from streamlit_folium import st_folium
+
+from utils.folium import (
+    draw_gdf,
+    get_clean_rendering_container,
+    get_map_crop,
+    get_parquet,
+)
+
+COLOR_MAP = {
+    "Grassland": "lime",
+    "Cereals": "saddlebrown",
+    "Other": "white",
+    "Flowers": "cyan",
+    "Vegetables": "purple",
+    "Fruit trees": "darkgreen",
+}
+
+
+id_class = {(i + 1): k for i, k in enumerate(COLOR_MAP.keys())}
+color_map_hex = {k: colors.to_hex(v) for k, v in COLOR_MAP.items()}
+id_map_hex = {(i + 1): v for i, v in enumerate(color_map_hex.values())}
+color_map_hex_r = {v: k for k, v in color_map_hex.items()}
+merged_list = list(itertools.chain(*list(color_map_hex_r.items())))
+
+
+def style_call(feat):
+    di = {
+        "fillColor": id_map_hex[feat["properties"]["class"]],
+        "fillOpacity": 0.7,
+        "color": id_map_hex[feat["properties"]["class"]],
+        "border-width": "thin",
+        "border-color": "#ffffff",
+        "weight": 1.2,
+    }
+    return di
+
+
+# Page configs
+st.set_page_config(page_title="AIDA", page_icon="🌐", layout="wide")
+
+# base paths
+base_path = Path("data")
+inference_path = base_path / "inference"
+
+# list examples and predictions
+inference_paths = sorted(list(inference_path.iterdir()))
+
+example_names = [p.stem for p in inference_paths]
+inference_dict = {p.stem: p for p in inference_paths}
+
+
+def change_key():
+    st.session_state["key_map"] = str(datetime.now())
+
+
+# Create selection menu
+container_predictions = st.container(border=True)
+with container_predictions:
+    col1, col2, col3 = st.columns([0.2, 0.1, 0.7])
+    with col1:
+        prediction_selectbox = st.selectbox(
+            "Select an example",
+            options=example_names,
+            index=None,
+            key="selectbox_pred",
+        )
+    is_prediction_selected = prediction_selectbox is not None
+    if is_prediction_selected:
+        try:
+            # add loading of the selected parquet prediction
+            chosen_tile_path = inference_dict[prediction_selectbox]
+            with open(chosen_tile_path, "rb") as f:
+                prediction_file = f.read()
+        except:
+            st.warning("File not found")
+            chosen_tile_path = None
+            prediction_file = None
+    else:
+        prediction_file = None
+        chosen_tile_path = None
+    with col2:
+        height_value = st.radio(
+            "Map height",
+            options=[800, 500],
+            horizontal=True,
+            key="height_map",
+            on_change=change_key,
+        )
+    with col3:
+        with st.container():
+            st.write("######")
+            with st.expander("See information about the methodology"):
+                st.write(
+                    """The model uses a modified UTAE architecture, a U-Net variant with attention, 
+                    for segmenting crop types from satellite imagery. 
+                    It was trained using Sentinel-2 time series data from several European countries, 
+                    labeled with aggregated Eurocrops data to identify 6 broad crop classes.
+                    More informations about the methodology [HERE](https://huggingface.co/links-ads/aida-cropland-models).
+                    Know more how this model was used in practice [HERE](https://business.esa.int/projects/aida)"""
+                )
+
+container = get_clean_rendering_container(prediction_selectbox)
+
+
+# Stange Hack to always update the map height I guess
+
+
+container = get_clean_rendering_container(height_value)
+
+# draw map
+interactive_map = get_map_crop()
+
+if prediction_selectbox is not None:
+    # draw prediction
+    draw_gdf(interactive_map, chosen_tile_path, "Prediction", style_call, id_class)
+
+
+with container.form(key="form1", clear_on_submit=True):
+
+    folium.LayerControl().add_to(interactive_map)
+    output_map = st_folium(
+        interactive_map,
+        width=None,
+        height=height_value,
+        returned_objects=["all_drawings"],
+        key=st.session_state.get("key_map", "key_map"),
+    )
+    submit = st.form_submit_button("Recenter map")
+
+# Update messages
+
+
+for name, path in inference_dict.items():
+    if path not in st.session_state.keys():
+        log.info(f"Loading parquet {name}")
+        st.session_state[path] = get_parquet(path, id_class)