Upload request_multiple_images_linux.py

File modified to get images 16-bits deep

request_multiple_images_linux.py

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+# -*- 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