area.py

#!/usr/bin/env python
# coding: utf-8

# This calculates the area of a raster by summing the squares
# of all pixel grids and grouping similar grids based on their rgb value


import rasterio

import os, sys
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from osgeo import gdal
import urllib.request


colors = {
    "157,198,116,255":"light_green",
    "235,237,140,255":"yellow",
    "86,160,92,255":"dark_green",
    "135,206,250,255":"blue"
}

def get_pixel_area(geo_file):
    with rasterio.open(geo_file) as raster:
        pixel_area = raster.res[0]*raster.res[1]
    
    return pixel_area

def get_color_distribution(raster_file):
    data = Image.open(raster_file)
    pixel_values = list(data.getdata())
    
    all_colors = {}

    for rgba in pixel_values:
        if ((0, 0, 0, 0) != rgba):
            key = ",".join([str(i) for i in rgba])
            if key in all_colors:
                all_colors[key] += 1
            else:
                all_colors[key] = 1
    return all_colors

def calculate_areas(pixel_area, distribution):
    area_sum = 0
    areas = {}
    for color in colors.items():
        areas[color[1]] = 0
        
    for item in distribution.items():
        area = item[1] * pixel_area
        area_sum += area
        areas[colors[item[0]]] = area
        
    return {"area_sum":area_sum, "areas":areas}


from flask import *

api = Flask(__name__)

@api.route('/get-area', methods=['GET', 'POST'])
def success():
    if request.method == 'POST':  
        tif_name = "last.tif"  
        save_path="./"+tif_name
#         print(request.files)
        tif = request.form["url"]
#         tif.save(save_path)
    else:
        tif = request.args.get("url")
    
    
    data = urllib.request.urlretrieve(tif)
    
    _tif = data[0]
    
    data_path_png = "./ras.png"
    data_path_tif = "./geo.tiff"

    gdal.Warp(data_path_tif, _tif, dstSRS="EPSG:3857")
    gdal.Translate(data_path_png, _tif)

    px_a = get_pixel_area(data_path_tif)
    col_dst = get_color_distribution(data_path_png)

    res = calculate_areas(px_a, col_dst)
    return  {"status":1, "result":res}

if __name__ == '__main__':
    api.run(host="0.0.0.0")