from xml.dom.minidom import Identified


def find_img_value(fieldid, satellite, imageType,bounds, from_date, to_date,CLIENT_ID,CLIENT_SECRET,INSTANCE_ID, max_num):
	from sentinelhub import WebFeatureService, BBox, CRS, DataSource, MimeType, CRS, BBox, WmsRequest,DataCollection
	from sentinelhub import SHConfig
	from firebase_admin import credentials
	from firebase_admin import db
	from statistics import mean
	from PIL import Image, ImageFilter
	import os.path
	import PIL
	import numpy as np
	import time

	#from scipy import ndimag
	config = SHConfig()
	print(imageType)
	img_values_arr = []
	cred = credentials.Certificate('servicekey2.json')
	access_key = 'AKIAIPCM5ZR7FRHMY3MA'
	secret_key = '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'
	if CLIENT_ID and CLIENT_SECRET:
		config.sh_client_id = CLIENT_ID
		config.sh_client_secret = CLIENT_SECRET
		config.instance_id = INSTANCE_ID
	img_width = 100
	search_bbox = BBox(bbox=bounds, crs=CRS.WGS84)
	search_time_interval = (from_date, to_date)
	avg_im = 0
	i = 0
	iterator_wms = WebFeatureService(search_bbox,search_time_interval,data_collection=satellite,maxcc=1.0,config=config)
	for tile_info in iterator_wms:
		print(tile_info["properties"]["date"])
		try:
			s1_request = WmsRequest(data_collection=satellite,layer=imageType,bbox=search_bbox,time=tile_info["properties"]["date"],width=img_width,image_format=MimeType.TIFF,config=config)
			s1_data = s1_request.get_data()
			im = s1_data[-1]
			new_dir = 'gt_input/'+ str(fieldid)
			file_name = new_dir + '/' + tile_info["properties"]["date"] + '.tiff'
			isdir = os.path.isdir(new_dir)
			if isdir != True:
				os.mkdir(new_dir)
			aqa = 1
			im = PIL.Image.fromarray(s1_data[-1])
			im.save(file_name)
			w,h = len(im[0]), len(im)
			#print(w,h)
			pixel_values = []
			z_num = 0
			for p in range(0,h-1):
				for q in range(0,w-1):
					pixel_value = im[p,q,0]
					if im[p,q,0] == 0:
						z_num = z_num + 1
					pixel_values.append(pixel_value)
			#im = PIL.Image.fromarray(s1_data[-1],"L")
			#im_array = np.array(im)
			avg_im = round(100*np.mean(pixel_values))/100
			if z_num < int(0.7*w*h):
				if i < max_num:
					img_values_arr.append(avg_im)
					i = i +1
				else:
					break
		except:
			adda = 1
		#print(avg_im)
	time.sleep(0.25)
	print(img_values_arr)
	if i < max_num:
		print(i)
		return None
	else:
		return img_values_arr