# !pip install geemap

import ee
import geemap

Map = geemap.Map()
Map

# point = ee.Geometry.Point([-122.4439, 37.7538])
point = ee.Geometry.Point([-87.7719, 41.8799])

image = (
    ee.ImageCollection("LANDSAT/LC08/C01/T1_SR")
    .filterBounds(point)
    .filterDate("2019-01-01", "2019-12-31")
    .sort("CLOUD_COVER")
    .first()
    .select("B[1-7]")
)

vis_params = {"min": 0, "max": 3000, "bands": ["B5", "B4", "B3"]}

Map.centerObject(point, 8)
Map.addLayer(image, vis_params, "Landsat-8")

props = geemap.image_props(image)
props.getInfo()

props.get("IMAGE_DATE").getInfo()

props.get("CLOUD_COVER").getInfo()

# region = Map.user_roi
# region = ee.Geometry.Rectangle([-122.6003, 37.4831, -121.8036, 37.8288])
# region = ee.Geometry.Point([-122.4439, 37.7538]).buffer(10000)

# Make the training dataset.
training = image.sample(
    **{
        #     'region': region,
        "scale": 30,
        "numPixels": 5000,
        "seed": 0,
        "geometries": True,  # Set this to False to ignore geometries
    }
)

Map.addLayer(training, {}, "training", False)
Map

# Instantiate the clusterer and train it.
n_clusters = 5
clusterer = ee.Clusterer.wekaKMeans(n_clusters).train(training)

# Cluster the input using the trained clusterer.
result = image.cluster(clusterer)

# # Display the clusters with random colors.
Map.addLayer(result.randomVisualizer(), {}, "clusters")
Map

legend_keys = ["One", "Two", "Three", "Four", "etc"]
legend_colors = ["#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3"]

# Reclassify the map
result = result.remap([0, 1, 2, 3, 4], [1, 2, 3, 4, 5])

Map.addLayer(
    result, {"min": 1, "max": 5, "palette": legend_colors}, "Labelled clusters"
)
Map.add_legend(
    legend_keys=legend_keys, legend_colors=legend_colors, position="bottomright"
)
Map

print("Change layer opacity:")
cluster_layer = Map.layers[-1]
cluster_layer.interact(opacity=(0, 1, 0.1))

import os

out_dir = os.path.join(os.path.expanduser("~"), "Downloads")
out_file = os.path.join(out_dir, "cluster.tif")

geemap.ee_export_image(result, filename=out_file, scale=90)

geemap.ee_export_image_to_drive(
    result, description="clusters", folder="export", scale=90
)