from PIL import Image
import numpy as np
from google.cloud import storage
import os
from firebase_admin import db
from get_mask import get_mask
import cv2
import scipy.ndimage
def make_area_estimation_image(arr, study_uid, study_field_id, threshold, latestDay, portion_num, row_num, col_num):
    num = 0
    row = 0
    column = 0
    m = 25
    storage_client = storage.Client()
    bucket_name = 'farmbase-b2f7e.appspot.com'

    map_fields = db.reference('PaidMonitoredFields').child('PMF').child(study_uid).child(study_field_id).get()
    coordinates = map_fields["Coordinates"]
    fieldmaxlat = map_fields["FieldMaxLat"]
    fieldminlat = map_fields["FieldMinLat"]
    fieldmaxlong = map_fields["FieldMaxLong"]
    fieldminlong = map_fields["FieldMinLong"]
    try:
        field_name = map_fields["FieldDescription"]
    except:
        field_name = map_fields["FieldAddress"]
    field_area = map_fields["FieldArea"]
    main_img_name = study_uid + "/" + study_field_id + "/area_estimate_ndvi_" + field_name + ".png"
    portion_img_name = study_uid + "/" + study_field_id + "/area_estimate_ndvi_" + field_name + "_"+ str(row_num)+ str(col_num)+ ".png"
    rvi_img = cv2.imread(main_img_name)
    h,w,c = rvi_img.shape
    data = np.zeros((h,w,3), dtype=np.uint8)
    new_rvi_data = data
    total_pixels = h*w
    area_pixels_arr = [0,0,0,0,0]
    area_pixels = 0
    
    #rvi_img = cv2.imread("area_estimate_rvi.tiff")

    #crops_rgb = [[0,255,255],[0,255,0],[255,0,0],[0,0,255],[0,0,0]]
    crops_rgb = [[0,0,0],[0,255,0]]
    #ranges = [[2,6],[6,10],[10,14],[14,18],[-2,2]]
    print('min_max',min(arr),max(arr))
    print(arr)
    # print(min(arr))
    for i in arr:
        if i >= threshold:
            area_pixels_arr[1] = area_pixels_arr[1] + 1
            data[row, column] = crops_rgb[1]
            new_rvi_data[row, column] = [rvi_img[row][column][2],rvi_img[row][column][1],rvi_img[row][column][0]]
            #data[row, column] = 1
            area_pixels = area_pixels + 1
        else:
            area_pixels_arr[0] = area_pixels_arr[0] + 1
            #data[row, column] = 0
            data[row, column] = crops_rgb[0]
            new_rvi_data[row, column] = crops_rgb[0]


        # new_img[row][column] = i
        column = column + 1
#		total_pixels =  total_pixels + 1
        if column%w == 0:
            row = row+1
            column = 0
    #print(row, column)

    #new_rvi_data = rvi_img
    #temp_rvi_img = new_rvi_data
    img = Image.fromarray(data, 'RGB')
    file_name = main_img_name
    #temp_rvi_img = Image.fromarray(new_rvi_data, 'RGB')
    #rvi_file_name = main_img_name
    isdir = os.path.isdir(study_uid)
    if isdir != True:
        os.mkdir(study_uid)
    img.save(file_name)
    img.save(portion_img_name)
    #temp_rvi_img.save(portion_img_name)
    latestDay = 0
    lastDayRef = db.reference('PaidMonitoredFields').child('PMF').child(study_uid).child(study_field_id).child('SensedDays').get()
    if latestDay == None:
        try:
            for (x,y) in lastDayRef.items():
                if int(x) > int(latestDay):
                    latestDay = x
        except:
            latestDay = 20202020
        latestDay = 10101010
    db.reference('PaidMonitoredFields').child('PMF').child(study_uid).child(study_field_id).child('SensedDays').child(str(latestDay)).set("yes")
    latestDay = str(latestDay)
    destination_blob_name_dem = 'PaidMonitoredFields/'+study_uid+'/'+study_field_id+'/'+latestDay+'/hybrid'
    dem_file_name = main_img_name
    
    new_area_pixels, new_total_pixels = get_mask(study_uid,study_field_id,coordinates,fieldmaxlat,fieldminlat,fieldmaxlong,fieldminlong, field_name)
    #crop_area = (area_pixels_arr[1]/(area_pixels_arr[0] + area_pixels_arr[1]))*int(field_area)
    crop_area = (new_area_pixels/new_total_pixels)*int(field_area)
    crop_area = int(crop_area/10000)
    print_text = (field_name + ' Area: ' + str(int(field_area/10000)) + ' Ha, Crop Area: ' + str(crop_area) + ' Ha')
    print(print_text)
    # try:
    #     db.reference('EgyptResults').child(field_name).set(print_text)
    # except:
    #     awa = 1
    bucket = storage_client.get_bucket(bucket_name)
    blob = bucket.blob(destination_blob_name_dem)
    blob.upload_from_filename(dem_file_name)