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if __name__ == "__main__":
  main(sys.argv[1])

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 img_path = sys.argv[1] 

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img_path = 'G:\\work\\earthquakes.jpg'

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# -*- coding: utf-8 -*-

import sys

import os

import math

from PIL import Image

 

# source path

img_path = sys.argv[1]



# tile size

tile_size = 256

 

# tile directory

tile_path = 'tiles'

 

 

def adjustBounds(src_img):

 

    # get size of original image

    src_width, src_height = src_img.size

 

    # calculate size of target image (background)

    target_width = src_width + (tile_size - src_width % tile_size)

    target_height = src_height + (tile_size - src_height % tile_size)

 

    # create transparent background

    target_img = Image.new('RGBA', (target_width, target_height))

 

    # combine original image and background

    target_img.paste(src_img, (0, 0))

 

    return target_img



img = Image.open(img_path)

w, h = img.size[0], img.size[1]

 

# calculate max zoom level

max_zoom = int(math.ceil(math.log((max(w, h) / tile_size), 2)))



# check world file path

if len(sys.argv) > 2:

    world_file = open(sys.argv[2])

    world_file_extension = sys.argv[2].split('.')[-1]

    affine_parameters = tuple(map(float, world_file))

 

for z in range(max_zoom, -1, -1):

 

    adjusted_image = adjustBounds(img)

 

    numcolumns = adjusted_image.size[0] / tile_size

    numrows = adjusted_image.size[1] / tile_size

 

    for x in range(numcolumns):

 

        # create z/x/ directory

        path = os.path.join(tile_path, str(z), str(x))

        if not os.path.isdir(path):

            os.makedirs(path)

 

        for y in range(numrows):

            bounds = (x * tile_size, y * tile_size, (x + 1) * tile_size, (y + 1) * tile_size)

            tile = adjusted_image.crop(bounds)

            tile.save('%s/%s.png' % (path, y))



            # create world file for each tile

            if world_file:

                wfile = open('%s/%s.%s' % (path, y, world_file_extension), 'wt')

                A = affine_parameters[0]

                C = affine_parameters[1]

                D = affine_parameters[2]

                B = affine_parameters[3]

                E = affine_parameters[4] + x*tile_size*A

                F = affine_parameters[5] + y*tile_size*B

                wfile.write("\n".join(map(str, [A, C, D, B, E, F])))

 

    w, h = img.size[0], img.size[1]

    img = img.resize((w / 2, h / 2), Image.ANTIALIAS)

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python tiling.py A20132742013304.L3m_MO_CHL_chlor_a_9km.png A20132742013304.L3m_MO_CHL_chlor_a_9km.wld

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gdal_translate -of PNG -scale A20132742013304.L3m_MO_CHL_chlor_a_9km.img A20132742013304.L3m_MO_CHL_chlor_a_9km.png

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gdal_translate -of HFA -outsize 50% 50% A20132742013304.L3m_MO_CHL_chlor_a_9km.img A20132742013304.L3m_MO_CHL_chlor_a_9km_resampled.img

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gdalwarp -of HFA -tr 0.16666666 0.16666666 A20132742013304.L3m_MO_CHL_chlor_a_9km.img A20132742013304.L3m_MO_CHL_chlor_a_9km_resampled.img