from socket import *
from oct2py import octave
from io import BytesIO
import base64
from make_area_estimation_image import make_area_estimation_image
from tempfile import tempdir
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
from find_s1_image2 import find_img_value
import pandas as pdf
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import statsmodels.api as sm
import seaborn as sns
sns.set()
import traceback
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
import csv
import time
import json
from find_modis_ndvi import find_modis_ndvi
import numpy as np
from sklearn.cluster import KMeans
from find_study_area_values import find_study_area_values
from find_study_area_values4 import find_study_area_values4
from make_area_estimate_image import make_area_estimate_image
from make_egypt_estimate_image import make_egypt_estimate_image
from sentinelhub import WebFeatureService, BBox, CRS, MimeType, CRS, BBox, WmsRequest,DataCollection
import traceback
from get_mask import get_mask
from PIL import Image
import numpy as np
from google.cloud import storage
from find_study_area_values import find_study_area_values
from find_study_area_values3 import find_study_area_values3
from make_area_estimate_image import make_area_estimate_image
from make_egypt_estimate_image import make_egypt_estimate_image
from make_area_estimation_image import make_area_estimation_image
cred = credentials.Certificate('servicekey.json')
x = 0.0003
y = 0.0003
fromdate = '20220701'
todate = '20220715'

s1_images = ['IW-VH-DB']
s1_images = ['NDVI']
s2_images = []
# s1_images = ["B02", "B03", "B04", "B05"]
#s2_images = ["RVI-NEW"]
try:
    firebase_admin.initialize_app(cred, {'databaseURL': 'https://farmbase-b2f7e-31c0c.firebaseio.com/'})
except:
    print('fire running')
#octave.make_gen_map1("uFfXgnVZ2zWp1mRaYjrBCfMUIw63")
arr = []
study_uid = 'uFfXgnVZ2zWp1mRaYjrBCfMUIw63'
study_field_id = '1677317171133'
threshold =0

make_area_estimation_image(arr, study_uid, study_field_id, threshold)