Export_sequence_image

import ee
import os

# Authenticate to your Earth Engine account
ee.Authenticate()
ee.Initialize(project='ee-davari2023')

# Define the Area of Interest (AOI) as a geometry (e.g., a point)
aoi = ee.Geometry.Point([-122.08412, 37.42189]) #ee.Geometry.Point([-7.547798, 38.653770]).buffer(1000)  # Longitude, Latitude

# Define the time period of interest
start_date = '2022-06-01'
end_date = '2022-06-30'

# Create an ImageCollection based on your criteria
##'COPERNICUS/S2 refers to the Sentinel-2 satellite imagery dataset
image_collection = ee.ImageCollection('COPERNICUS/S2') \
    .filterBounds(aoi) \
    .filterDate(start_date, end_date) \
    .sort('CLOUDY_PIXEL_PERCENTAGE')


# Specify the folder where you want to save the images
download_folder = 'images_Portugal_1'

# Create the download folder if it doesn't exist
os.makedirs(download_folder, exist_ok=True)

# Loop through the images in the ImageCollection and download them
image_list = image_collection.toList(image_collection.size())
for i in range(2): #image_list.size().getInfo()
    image = ee.Image(image_list.get(i))
    image_id = image.id().getInfo()
    #image = image.toUint16()
    name = image.get('system:index').getInfo()
    #image_filename = os.path.join(download_folder, f'image_{image_id}.png')
    # Export the image to your local folder
    ## Bands 4, 3, and 2 are often used for RGB images
    task = ee.batch.Export.image.toDrive(image=image.select(['B4', 'B3', 'B2']), description=image_id, folder=download_folder, scale= 30)
    # Check the task status
    task_status = task.status()
    has_retries = task_status["state"] == "FAILED" and task_status["error_message"] is not None

    # Print the result
    if has_retries:
        print("The task has been retried.")
    else:
        print("The task has not been retried.")
    task.start()
    print(i)