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import os
from datetime import datetime
from pathlib import Path
import torch
import folium
import streamlit as st
from loguru import logger
from tqdm import tqdm
from streamlit_folium import st_folium
from transformers import SegformerForSemanticSegmentation
from lib.folium import (
get_clean_rendering_container,
create_map,
process_raster_and_overlays,
)
import streamlit.components.v1 as components
# Page configs
st.set_page_config(page_title="GrowSeg Demo", page_icon="🍇", layout="wide")
# BUGFIX (https://discuss.streamlit.io/t/message-error-about-torch/90886/6)
torch.classes.__path__ = []
# Interoperability with tqdm (https://loguru.readthedocs.io/en/stable/resources/recipes.html#interoperability-with-tqdm-iterations)
logger.remove()
logger.add(lambda msg: tqdm.write(msg, end=""), colorize=True, format="<green>{message}</green>")
@st.cache_resource
def load_model(hf_path='links-ads/gaia-growseg'):
# logger.info(f'Loading GAIA GRowSeg on {device}...')
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = SegformerForSemanticSegmentation.from_pretrained(
hf_path,
num_labels=1,
num_channels=3,
id2label={1: 'vine'},
label2id={'vine': 1},
token=os.getenv('hf_read_access_token')
)
return model.to(device).eval()
# Load GAIA GRowSeg model
model = load_model()
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 = st.columns([0.3, 0.7])
with col1:
# raster_path = st.text_input(
# "Enter the path to your local file: ",
# key="raster_path_block",
# )
# raster_path = st.file_uploader(
# "Upload a raster file",
# type=["tif", "tiff"],
# key="raster_path_block",
# )
precomputed_map_path = None
raster_path = None
raster_selection = st.selectbox(
"Select an example or your own raster...",
options=[
"Italy",
"Portugal",
"Spain",
"Upload file...",
],
key="raster_selection_block",
index=None,
placeholder="Choose an example or upload your own raster",
)
if raster_selection == "Italy":
st.markdown("At this stage, only Portugal is available due to the WebSocket payload limit.")
# TODO GEOSERVER
#precomputed_map_path = "data/italy_2022-06-13_cropped.html"
elif raster_selection == "Portugal":
precomputed_map_path = "data/portugal_2023-08-01.html"
elif raster_selection == "Spain":
st.markdown("At this stage, only Portugal is available due to the WebSocket payload limit.")
#precomputed_map_path = "data/spain_2022-07-29_cropped.html"
elif raster_selection == "Upload file...":
uploaded_file = st.file_uploader(
"Upload a raster file",
type=["tif"],
key="uploaded_file_block",
)
if uploaded_file is not None:
fn = Path(uploaded_file.name).name
print(fn)
raster_path = os.path.join("temp", fn)
with open(raster_path, "wb") as f:
f.write(uploaded_file.getbuffer())
is_raster_path_selected = raster_path is not None
is_precomputed_map_selected = precomputed_map_path is not None
with col2:
with st.container():
st.write("######")
with st.expander("More info on the model"):
st.write("""
Under the hood, this model is a SegFormer-b5, trained on
UAV-acquired vineyard orthoimages and their ground-truth
delineation masks. Paper will be available soon. Stay tuned!
""")
if not is_precomputed_map_selected and is_raster_path_selected:
progress_bar = st.progress(0, text="Begin processing...")
# Process raster and get overlays
overlays = process_raster_and_overlays(raster_path, model, _progress_bar=progress_bar)
#progress_bar.empty()
#container = get_clean_rendering_container(raster_path)
container = st.empty()
# draw map
interactive_map = create_map()
if is_raster_path_selected:
# Add overlays to map
for overlay in overlays:
overlay.add_to(interactive_map)
with container.form(key="form1"):
if is_precomputed_map_selected:
# Load precomputed map
# interactive_map = folium.Map(location=[35, -10], zoom_start=6)
# folium.IFrame(
# precomputed_map_path,
# width=1000,
# height=500,
# ).add_to(interactive_map)
with open(precomputed_map_path, 'r') as f:
html_content = f.read()
interactive_map = components.html(html_content, height=500)
else:
if is_raster_path_selected:
# Center map on overlays
bounds = overlays[0].get_bounds()
interactive_map.fit_bounds(bounds)
else:
# Center map on Europe
interactive_map.fit_bounds([[35, -10], [60, 40]])
# Add Layer Control (first remove existing one)
for key, child in list(interactive_map._children.items()):
if isinstance(child, folium.map.LayerControl):
del interactive_map._children[key]
folium.LayerControl().add_to(interactive_map)
# Folium Map component
output_map = st_folium(
interactive_map,
width=None,
height=500,
returned_objects=["all_drawings"],
key=st.session_state.get("key_map", "key_map"), # This is a workaround to force the map to recenter
)
# Recenter map
submit = st.form_submit_button("Recenter map")
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