request_multiple_images_linux.py

# -*- coding: utf-8 -*-

'''
Author: Sebastian Cajas

We recommend to use eo-learn for more complex cases where you need multiple timestamps or high-resolution data for larger areas.
https://github.com/sentinel-hub/eo-learn

!pip install epiweeks


'''

from sentinelhub import SHConfig
import os
import datetime
import numpy as np
import matplotlib.pyplot as plt
import sys
from datetime import timedelta
sys.path.insert(0,'..') 
from sentinelhub import MimeType, CRS, BBox, SentinelHubRequest, SentinelHubDownloadClient, DataCollection, bbox_to_dimensions, DownloadRequest
#from rename_linux import *
from epiweeks import Week, Year
from datetime import date
import glob, shutil

def cleaners(dataset, root_images):
 for root, dirs, files in os.walk(dataset, topdown=True):
 for name in files:
 path = os.path.join(root, name)
 if ".tiff" in path:
 os.remove(path)
 
 
 return print("Ready")

def get_epi_weeks(start):
 

 tdelta = timedelta(days = 7)

 
 edges = [(start + i*tdelta) for i in range(2)]
 
 
 return [(edges[i], edges[i+1]) for i in range(len(edges)-1)]
 

def plot_image(image, factor=1.0, clip_range = None, **kwargs):
 """
 Utility function for plotting RGB images.
 """
 fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15, 15))
 if clip_range is not None:
 ax.imshow(np.clip(image * factor, *clip_range), **kwargs)
 else:
 ax.imshow(image * factor, **kwargs)
 ax.set_xticks([])
 ax.set_yticks([])

def download_multiple_images(coordinates, start, year, CLIENT_ID, CLIENT_SECRET):

 # put here your credentials
 CLIENT_ID = CLIENT_ID
 CLIENT_SECRET = CLIENT_SECRET

 config = SHConfig()

 if CLIENT_ID and CLIENT_SECRET:
 config.sh_client_id = CLIENT_ID
 config.sh_client_secret=CLIENT_SECRET
 
 if not config.sh_client_id or not config.sh_client_secret:
 print("Warning! To use Process API, please provide the credentials (OAuth client ID and client secret).")

 resolution = 10
 bbox = BBox(bbox=coordinates, crs=CRS.WGS84)
 bbox_size = bbox_to_dimensions(bbox, resolution=resolution)

 #print(f'Image shape at {resolution} m resolution: {bbox_size} pixels')

 slots = get_epi_weeks(start)
 
 # Visualization purposes
 d_init = slots[0][0].strftime('%m/%d/%Y')
 d_end = slots[0][1].strftime('%m/%d/%Y')
 print(f"Requested week slot: {d_init} - {d_end} ")


 script_Medellin = """

 //VERSION=3
 function setup() {
 return {
 input: [{
 bands: ["B01", "B02", "B03", "B04", "B05", "B06", "B07", "B08", "B8A", "B09", "B10", "B11", "B12"],
 units: "DN"
 }],
 output: {
 id: "default",
 bands: 12,
 sampleType: SampleType.UINT16
 }
 }
 }

 function evaluatePixel(sample) {
 return [ sample.B01, sample.B02, sample.B03, sample.B04, sample.B05, sample.B06, sample.B07, sample.B08, sample.B8A, sample.B09, sample.B10, sample.B11, sample.B12]
 }
 """
 

 '''Check if directory exists, if not, create it'''
 
 # You should change 'test' to your preferred folder.
 # If folder doesn't exist, then create it.
 
 # if windows: 
 path = os.path.abspath(os.getcwd()) + "//data" + "//" + year
 # if linux: path = os.path.abspath(os.getcwd()) + "/data" + "/" year
 
 if not os.path.isdir(path):
 os.makedirs(path)
 #print("created folder : ", path)
 else:
 #print(path, "Folder already exists. Rewriting*")
 pass
 
 def get_true_color_request(time_interval):
 return SentinelHubRequest(
 data_folder= 'data' + "/" + year,
 evalscript=script_Medellin,
 input_data=[
 SentinelHubRequest.input_data(
 data_collection=DataCollection.SENTINEL2_L1C,
 #time_interval=('2015-11-1', '2015-11-20'), #time_interval,
 time_interval=time_interval,
 mosaicking_order='leastCC'
 )
 ],
 responses=[
 SentinelHubRequest.output_response('default', MimeType.TIFF)
 ],
 bbox=bbox,
 size=bbox_size,
 config=config
 )

 # create a list of requests
 list_of_requests = [get_true_color_request(slot) for slot in slots]
 list_of_requests = [request.download_list[0] for request in list_of_requests]

 image = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
 print("Ended downloading")

 # Verify if images are empty, if not, correct
 img = np.array(image)
 #with open('readme.txt', 'w') as f:
 # f.write(img.shape)
 
 print(img.shape)
 print(img.max())
 
 # Verify if images are empty, if not, correct
 if img.sum() == 0:
 print("Image empty: ", img.sum())
 # Initialize 
 end = slots[0][1]
 # Add delay by 1 day step
 while img.sum() == 0: # tune
 tdelta = timedelta(days = 1)
 init = slots[0][0]
 end = end + tdelta
 corrected_slot = [(init, end)]
 #print("Slot corrected to: ", corrected_slot)
 list_of_requests = [get_true_color_request(slot) for slot in corrected_slot]
 
 list_of_requests = [request.download_list[0] for request in list_of_requests]
 image = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
 img = np.array(image)
 print("This image is being replaced..")
 print("Slot corrected to: ", corrected_slot)
 
 
 else:
 print(f"Pixel values: ", np.unique(img))
 pass

 '''
 # Remove extra dimension
 img = np.squeeze(image, axis = 0)
 
 ncols = 4
 nrows = 3

 aspect_ratio = bbox_size[0] / bbox_size[1]
 subplot_kw = {'xticks': [], 'yticks': [], 'frame_on': False}

 plot_image(img[:,:,1], factor=1.0, cmap=plt.cm.Greys_r, vmin=0, vmax=120)
 '''
 return img

def get_folder_ID(root_images, img_format):
 
 walker = "." + root_images
 
 for root, dirs, files in os.walk(walker, topdown=True):
 for name in files:
 path = os.path.join(root, name)
 if "response" in path:
 
 folder_path = path.replace("/" + "response." + img_format, "")

 return folder_path