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Merge branch 'release/v1.2.0' into streamlit-app
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@IndigoWizard
IndigoWizard committed Oct 31, 2023
2 parents 1694eb9 + 318a8a3 commit 03b6bb0
Showing 1 changed file with 70 additions and 71 deletions.
141 changes: 70 additions & 71 deletions app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -134,6 +134,11 @@
background: rgba(0, 0, 0, 0.12);
cursor: pointer;
}
/*Form submit button: generate map*/
button.st-emotion-cache-19rxjzo:nth-child(1) {
width: 100%;
}
</style>
""", unsafe_allow_html=True)

Expand Down Expand Up @@ -257,70 +262,71 @@ def main():
st.markdown("**Monitor Vegetation Health by Viewing & Comparing NDVI Values Through Time and Location with Sentinel-2 Satellite Images on The Fly!**")

# columns for input - map
c1, c2 = st.columns([3, 1])
#### User input section - START

with st.container():
with c2:
## Cloud coverage input
st.info("Cloud Coverage 🌥️")
cloud_pixel_percentage = st.slider(label="cloud pixel rate", min_value=5, max_value=100, step=5, value=75 , label_visibility="collapsed")

## File upload
# User input GeoJSON file
st.info("Upload Area Of Interest file:")
upload_files = st.file_uploader("Crete a GeoJSON file at: [geojson.io](https://geojson.io/)", accept_multiple_files=True)
# calling upload files function
geometry_aoi = upload_files_proc(upload_files)
with st.form("input_form"):
c1, c2 = st.columns([3, 1])
#### User input section - START

## Accessibility: Color palette input
st.info("Custom Color Palettes")
accessibility = st.selectbox("Accessibility: Colorblind-friendly Palettes", ["Normal", "Deuteranopia", "Protanopia", "Tritanopia", "Achromatopsia"])

# Define default color palettes: used in map layers & map legend
default_ndvi_palette = ["#ffffe5", "#f7fcb9", "#78c679", "#41ab5d", "#238443", "#005a32"]
default_reclassified_ndvi_palette = ["#a50026","#ed5e3d","#f9f7ae","#f4ff78","#9ed569","#229b51","#006837"]
with st.container():
with c2:
## Cloud coverage input
st.info("Cloud Coverage 🌥️")
cloud_pixel_percentage = st.slider(label="cloud pixel rate", min_value=5, max_value=100, step=5, value=85 , label_visibility="collapsed")

## File upload
# User input GeoJSON file
st.info("Upload Area Of Interest file:")
upload_files = st.file_uploader("Crete a GeoJSON file at: [geojson.io](https://geojson.io/)", accept_multiple_files=True)
# calling upload files function
geometry_aoi = upload_files_proc(upload_files)

# a copy of default colors that can be reaffected
ndvi_palette = default_ndvi_palette.copy()
reclassified_ndvi_palette = default_reclassified_ndvi_palette.copy()

if accessibility == "Deuteranopia":
ndvi_palette = ["#fffaa1","#f4ef8e","#9a5d67","#573f73","#372851","#191135"]
reclassified_ndvi_palette = ["#95a600","#92ed3e","#affac5","#78ffb0","#69d6c6","#22459c","#000e69"]
elif accessibility == "Protanopia":
ndvi_palette = ["#a6f697","#7def75","#2dcebb","#1597ab","#0c677e","#002c47"]
reclassified_ndvi_palette = ["#95a600","#92ed3e","#affac5","#78ffb0","#69d6c6","#22459c","#000e69"]
elif accessibility == "Tritanopia":
ndvi_palette = ["#cdffd7","#a1fbb6","#6cb5c6","#3a77a5","#205080","#001752"]
reclassified_ndvi_palette = ["#ed4700","#ed8a00","#e1fabe","#99ff94","#87bede","#2e40cf","#0600bc"]
elif accessibility == "Achromatopsia":
ndvi_palette = ["#407de0", "#2763da", "#394388", "#272c66", "#16194f", "#010034"]
reclassified_ndvi_palette = ["#004f3d", "#338796", "#66a4f5", "#3683ff", "#3d50ca", "#421c7f", "#290058"]
## Accessibility: Color palette input
st.info("Custom Color Palettes")
accessibility = st.selectbox("Accessibility: Colorblind-friendly Palettes", ["Normal", "Deuteranopia", "Protanopia", "Tritanopia", "Achromatopsia"])

with st.container():
## Time range input
with c1:
col1, col2 = st.columns(2)

# Creating a 2 days delay for the date_input placeholder to be sure there are satellite images in the dataset on app start
today = datetime.today()
delay = today - timedelta(days=2)
# Define default color palettes: used in map layers & map legend
default_ndvi_palette = ["#ffffe5", "#f7fcb9", "#78c679", "#41ab5d", "#238443", "#005a32"]
default_reclassified_ndvi_palette = ["#a50026","#ed5e3d","#f9f7ae","#f4ff78","#9ed569","#229b51","#006837"]

# a copy of default colors that can be reaffected
ndvi_palette = default_ndvi_palette.copy()
reclassified_ndvi_palette = default_reclassified_ndvi_palette.copy()

if accessibility == "Deuteranopia":
ndvi_palette = ["#fffaa1","#f4ef8e","#9a5d67","#573f73","#372851","#191135"]
reclassified_ndvi_palette = ["#95a600","#92ed3e","#affac5","#78ffb0","#69d6c6","#22459c","#000e69"]
elif accessibility == "Protanopia":
ndvi_palette = ["#a6f697","#7def75","#2dcebb","#1597ab","#0c677e","#002c47"]
reclassified_ndvi_palette = ["#95a600","#92ed3e","#affac5","#78ffb0","#69d6c6","#22459c","#000e69"]
elif accessibility == "Tritanopia":
ndvi_palette = ["#cdffd7","#a1fbb6","#6cb5c6","#3a77a5","#205080","#001752"]
reclassified_ndvi_palette = ["#ed4700","#ed8a00","#e1fabe","#99ff94","#87bede","#2e40cf","#0600bc"]
elif accessibility == "Achromatopsia":
ndvi_palette = ["#407de0", "#2763da", "#394388", "#272c66", "#16194f", "#010034"]
reclassified_ndvi_palette = ["#004f3d", "#338796", "#66a4f5", "#3683ff", "#3d50ca", "#421c7f", "#290058"]

with st.container():
## Time range input
with c1:
col1, col2 = st.columns(2)

# Creating a 2 days delay for the date_input placeholder to be sure there are satellite images in the dataset on app start
today = datetime.today()
delay = today - timedelta(days=2)

# Date input widgets
col1.warning("Initial NDVI Date 📅")
initial_date = col1.date_input("initial", value=delay, label_visibility="collapsed")
# Date input widgets
col1.warning("Initial NDVI Date 📅")
initial_date = col1.date_input("initial", value=delay, label_visibility="collapsed")

col2.success("Updated NDVI Date 📅")
updated_date = col2.date_input("updated", value=delay, label_visibility="collapsed")
col2.success("Updated NDVI Date 📅")
updated_date = col2.date_input("updated", value=delay, label_visibility="collapsed")

# Setting up the time range variable for an image collection
time_range = 7
# Process initial date
str_initial_start_date, str_initial_end_date = date_input_proc(initial_date, time_range)
# Setting up the time range variable for an image collection
time_range = 7
# Process initial date
str_initial_start_date, str_initial_end_date = date_input_proc(initial_date, time_range)

# Process updated date
str_updated_start_date, str_updated_end_date = date_input_proc(updated_date, time_range)
# Process updated date
str_updated_start_date, str_updated_end_date = date_input_proc(updated_date, time_range)

#### User input section - END

Expand All @@ -346,19 +352,6 @@ def main():
b1 = folium.TileLayer('cartodbdark_matter', name='Dark Basemap')
b1.add_to(m)

## WMS tiles basemaps
# OSM CyclOSM basemap
# b2 = WmsTileLayer(
# url=('https://{s}.tile-cyclosm.openstreetmap.fr/cyclosm/{z}/{x}/{y}.png'),
# layers=None,
# name='Topography Basemap', # layer name to display on layer panel
# attr='Topography Map',
# show=False
# )
# b2.add_to(m)
### BASEMAPS - END
#### Map section - END

#### Satellite imagery Processing Section - START
## Defining and clipping image collections for both dates:
# initial Image collection
Expand Down Expand Up @@ -464,7 +457,13 @@ def classify_ndvi(masked_image): # better use a masked image to avoid water bodi
# Folium Map Layer Control: we can see and interact with map layers
folium.LayerControl(collapsed=True).add_to(m)
# Display the map
folium_static(m)
submitted = c2.form_submit_button("Generate map")
if submitted:
with c1:
folium_static(m)
else:
with c1:
folium_static(m)

#### Map result display - END

Expand Down

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