#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ICIAR2018 - Grand Challenge on Breast Cancer Histology Images
https://iciar2018-challenge.grand-challenge.org/home/
"""

import openslide
from matplotlib import pyplot as plt
from openslide import open_slide # http://openslide.org/api/python/
import numpy as np
import os


save = True

dir_img = 'PATH TO THE DATASET FOLDER'
dir_img = '/home/ubuntu/thesis/data/ICIA2018/ICIAR2018_BACH_Challenge/WSI/'

valid_images = ['.svs']

patch_size = (1024,1024)

for f in os.listdir(dir_img):
    ext = os.path.splitext(f)[1]
    if ext.lower() not in valid_images:
        continue
    curr_path = os.path.join(dir_img,f)
    print(curr_path)
    
    # open scan
    scan = openslide.OpenSlide(curr_path)
    
    orig_w = np.int64(scan.properties.get('aperio.OriginalWidth'))
    orig_h = np.int64(scan.properties.get('aperio.OriginalHeight'))
    
    # create an array to store our image
    img_np = np.zeros((orig_w,orig_h,3),dtype=np.uint8)

    for r in range(0,orig_w,patch_size[0]):
        for c in range(0, orig_h,patch_size[1]):
            if c+patch_size[1] > orig_h and r+patch_size[0]<= orig_w:
                p = orig_h-c
                img = np.array(scan.read_region((c,r),0,(p,patch_size[1])),dtype=np.uint8)[...,0:3]
            elif c+patch_size[1] <= orig_h and r+patch_size[0] > orig_w:
                p = orig_w-r
                img = np.array(scan.read_region((c,r),0,(patch_size[0],p)),dtype=np.uint8)[...,0:3]
            elif  c+patch_size[1] > orig_h and r+patch_size[0] > orig_w:
                p = orig_h-c
                pp = orig_w-r
                img = np.array(scan.read_region((c,r),0,(p,pp)),dtype=np.uint8)[...,0:3]
            else:    
                img = np.array(scan.read_region((c,r),0,(patch_size[0],patch_size[1])),dtype=np.uint8)[...,0:3]
            img_np[r:r+patch_size[0],c:c+patch_size[1]] = img


    if save:
        name_no_ext = os.path.splitext(f)[0]
        np.save(dir_img + name_no_ext, img_np)
        
    scan.close