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extract_patches.py
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import glob
import os
import sys
import cv2
import matplotlib.pyplot as plt
import numpy as np
import camelyon16.utils as utils
from camelyon16.ops.wsi_ops import PatchExtractor
from camelyon16.ops.wsi_ops import WSIOps
def extract_positive_patches_from_tumor_wsi(wsi_paths, mask_paths, wsi_ops, patch_extractor, patch_index,
augmentation=False):
image_mask_pair = zip(wsi_paths, mask_paths)
image_mask_pair = list(image_mask_pair)
# image_mask_pair = image_mask_pair[67:68]
patch_save_dir = utils.PATCHES_TUMOR_POSITIVE_PATH
patch_prefix = utils.PATCH_TUMOR_PREFIX
for image_path, mask_path in image_mask_pair:
print('extract_positive_patches_from_tumor_wsi(): %s' % utils.get_filename_from_path(image_path))
wsi_image, rgb_image, wsi_mask, tumor_gt_mask, level_used = wsi_ops.read_wsi_tumor(image_path, mask_path)
assert wsi_image is not None, 'Failed to read Whole Slide Image %s.' % image_path
bounding_boxes = wsi_ops.find_roi_bbox_tumor_gt_mask(np.array(tumor_gt_mask))
patch_index = patch_extractor.extract_positive_patches_from_tumor_region(wsi_image, np.array(tumor_gt_mask),
level_used, bounding_boxes,
patch_save_dir, patch_prefix,
patch_index, wsi_mask)
# print('Positive patch count: %d' % (patch_index - utils.PATCH_INDEX_POSITIVE))
wsi_image.close()
def extract_negative_patches_from_tumor_wsi(wsi_paths, mask_paths, wsi_ops, patch_extractor, patch_index, augmentation=False):
image_mask_pair = zip(wsi_paths, mask_paths)
image_mask_pair = list(image_mask_pair)
# image_mask_pair = image_mask_pair[67:68]
patch_save_dir = utils.PATCHES_TUMOR_NEGATIVE_PATH
patch_prefix = utils.PATCH_NORMAL_PREFIX
for image_path, mask_path in image_mask_pair:
print('extract_negative_patches_from_tumor_wsi(): %s' % utils.get_filename_from_path(image_path))
wsi_image, rgb_image, _, tumor_gt_mask, level_used = wsi_ops.read_wsi_tumor(image_path, mask_path)
assert wsi_image is not None, 'Failed to read Whole Slide Image %s.' % image_path
bounding_boxes, rgb_contour, image_open = wsi_ops.find_roi_bbox(np.array(rgb_image))
patch_index = patch_extractor.extract_negative_patches_from_tumor_wsi(wsi_image, np.array(tumor_gt_mask),
image_open, level_used,
bounding_boxes, patch_save_dir,
patch_prefix,
patch_index)
wsi_image.close()
return patch_index
def extract_patches_from_heatmap_false_region_tumor(wsi_ops, patch_extractor, patch_index, augmentation=False):
tumor_heatmap_prob_paths = glob.glob(os.path.join(utils.HEAT_MAP_DIR, '*umor*prob.png'))
tumor_heatmap_prob_paths.sort()
wsi_paths = glob.glob(os.path.join(utils.TUMOR_WSI_PATH, '*.tif'))
wsi_paths.sort()
mask_paths = glob.glob(os.path.join(utils.TUMOR_MASK_PATH, '*.tif'))
mask_paths.sort()
assert len(tumor_heatmap_prob_paths) == len(wsi_paths), 'Some heatmaps are missing!'
image_mask_heatmap_tuple = zip(wsi_paths, mask_paths, tumor_heatmap_prob_paths)
image_mask_heatmap_tuple = list(image_mask_heatmap_tuple)
# image_mask_heatmap_tuple = image_mask_heatmap_tuple[32:]
# delete Tumor slides with mirror(duplicate regions) and incomplete annotation: Tumor_018, Tumor_046, Tumor_054
delete_index = [17, 45, 53]
for i in range(len(delete_index)):
print('deleting: %s' % utils.get_filename_from_path(image_mask_heatmap_tuple[delete_index[i] - i][0]))
del image_mask_heatmap_tuple[delete_index[i] - i]
patch_save_dir_pos = utils.PATCHES_TRAIN_AUG_EXCLUDE_MIRROR_WSI_POSITIVE_PATH if augmentation else utils.PATCHES_TRAIN_POSITIVE_PATH
patch_prefix_pos = utils.PATCH_AUG_TUMOR_PREFIX if augmentation else utils.PATCH_TUMOR_PREFIX
patch_save_dir_neg = utils.PATCHES_TRAIN_AUG_EXCLUDE_MIRROR_WSI_NEGATIVE_PATH if augmentation else utils.PATCHES_TRAIN_NEGATIVE_PATH
patch_prefix_neg = utils.PATCH_AUG_NORMAL_PREFIX if augmentation else utils.PATCH_NORMAL_PREFIX
not_0_255_cnt = 0
for image_path, mask_path, heatmap_prob_path in image_mask_heatmap_tuple:
print('extract_patches_from_heatmap_false_region_normal(): %s, %s, %s' %
(utils.get_filename_from_path(image_path), utils.get_filename_from_path(mask_path),
utils.get_filename_from_path(heatmap_prob_path)))
wsi_image, rgb_image, wsi_mask, tumor_gt_mask, level_used = wsi_ops.read_wsi_tumor(image_path, mask_path)
assert wsi_image is not None, 'Failed to read Whole Slide Image %s.' % image_path
# tumor_gt_mask = cv2.cvtColor(tumor_gt_mask, cv2.COLOR_BGR2GRAY)
# not_0_255_cnt += (tumor_gt_mask[tumor_gt_mask != 255].shape[0]-tumor_gt_mask[tumor_gt_mask == 0].shape[0])
# print(tumor_gt_mask[tumor_gt_mask != 255].shape[0], tumor_gt_mask[tumor_gt_mask == 0].shape[0], not_0_255_cnt)
bounding_boxes, image_open = wsi_ops.find_roi_bbox(np.array(rgb_image))
heatmap_prob = cv2.imread(heatmap_prob_path)
heatmap_prob = heatmap_prob[:, :, :1]
heatmap_prob = np.reshape(heatmap_prob, (heatmap_prob.shape[0], heatmap_prob.shape[1]))
heatmap_prob = np.array(heatmap_prob, dtype=np.float32)
heatmap_prob /= 255
patch_index = patch_extractor.extract_patches_from_heatmap_false_region_tumor(wsi_image, wsi_mask,
tumor_gt_mask,
image_open,
heatmap_prob,
level_used, bounding_boxes,
patch_save_dir_pos,
patch_save_dir_neg,
patch_prefix_pos,
patch_prefix_neg,
patch_index)
print('patch count: %d' % (patch_index - utils.PATCH_INDEX_NEGATIVE))
wsi_image.close()
wsi_mask.close()
# print('not_0_255_cnt: %d' % not_0_255_cnt)
return patch_index
def extract_patches_from_heatmap_false_region_normal(wsi_ops, patch_extractor, patch_index, augmentation=False):
normal_heatmap_prob_paths = glob.glob(os.path.join(utils.HEAT_MAP_DIR, 'Normal*prob.png'))
normal_heatmap_prob_paths.sort()
wsi_paths = glob.glob(os.path.join(utils.NORMAL_WSI_PATH, '*.tif'))
wsi_paths.sort()
assert len(normal_heatmap_prob_paths) == len(wsi_paths), 'Some heatmaps are missing!'
image_heatmap_tuple = zip(wsi_paths, normal_heatmap_prob_paths)
image_heatmap_tuple = list(image_heatmap_tuple)
# image_mask_pair = image_mask_pair[67:68]
patch_save_dir_neg = utils.PATCHES_TRAIN_AUG_NEGATIVE_PATH if augmentation else utils.PATCHES_TRAIN_NEGATIVE_PATH
patch_prefix_neg = utils.PATCH_AUG_NORMAL_PREFIX if augmentation else utils.PATCH_NORMAL_PREFIX
for image_path, heatmap_prob_path in image_heatmap_tuple:
print('extract_patches_from_heatmap_false_region_normal(): %s, %s' % (utils.get_filename_from_path(image_path)
, utils.get_filename_from_path(
heatmap_prob_path)))
wsi_image, rgb_image, level_used = wsi_ops.read_wsi_normal(image_path)
assert wsi_image is not None, 'Failed to read Whole Slide Image %s.' % image_path
bounding_boxes, image_open = wsi_ops.find_roi_bbox(np.array(rgb_image))
heatmap_prob = cv2.imread(heatmap_prob_path)
heatmap_prob = heatmap_prob[:, :, :1]
heatmap_prob = np.reshape(heatmap_prob, (heatmap_prob.shape[0], heatmap_prob.shape[1]))
heatmap_prob = np.array(heatmap_prob, dtype=np.float32)
heatmap_prob /= 255
patch_index = patch_extractor.extract_patches_from_heatmap_false_region_normal(wsi_image,
image_open,
heatmap_prob,
level_used, bounding_boxes,
patch_save_dir_neg,
patch_prefix_neg,
patch_index)
print('patch count: %d' % (patch_index - utils.PATCH_INDEX_NEGATIVE))
wsi_image.close()
return patch_index
def extract_negative_patches_from_normal_wsi(wsi_paths, wsi_ops, patch_extractor, patch_index, augmentation=False):
"""
Extracted up to Normal_060.
:param wsi_ops:
:param patch_extractor:
:param patch_index:
:param augmentation:
:return:
"""
# wsi_paths = glob.glob(os.path.join(utils.NORMAL_WSI_PATH, '*.tif'))
# wsi_paths.sort()
# wsi_paths = wsi_paths[61:]
patch_save_dir = utils.PATCHES_NORMAL_NEGATIVE_PATH
patch_prefix = utils.PATCH_NORMAL_PREFIX
for image_path in wsi_paths:
print('extract_negative_patches_from_normal_wsi(): %s' % utils.get_filename_from_path(image_path))
wsi_image, rgb_image, level_used = wsi_ops.read_wsi_normal(image_path)
assert wsi_image is not None, 'Failed to read Whole Slide Image %s.' % image_path
bounding_boxes, rgb_contour, image_open = wsi_ops.find_roi_bbox(np.array(rgb_image))
patch_index = patch_extractor.extract_negative_patches_from_normal_wsi(wsi_image, image_open,
level_used,
bounding_boxes,
patch_save_dir, patch_prefix,
patch_index)
wsi_image.close()
return patch_index
def extract_patches(ops, pe):
patch_index_positive = utils.PATCH_INDEX_POSITIVE
patch_index_negative = utils.PATCH_INDEX_NEGATIVE
# patch_index_negative = extract_negative_patches_from_tumor_wsi(ops, pe, patch_index_negative)
# extract_negative_patches_from_normal_wsi(ops, pe, patch_index_negative)
# extract_positive_patches_from_tumor_wsi(ops, pe, patch_index_positive)
def extract_patches_augmented(ops, pe):
patch_index_positive = utils.PATCH_INDEX_POSITIVE
patch_index_negative = utils.PATCH_INDEX_NEGATIVE
# index - 500000
# index - 700000 -> remove wrong false positives
patch_index_negative = extract_patches_from_heatmap_false_region_tumor(ops, pe, patch_index_negative,
augmentation=True)
# index - 600000
# patch_index_negative = extract_patches_from_heatmap_false_region_normal(ops, pe, patch_index_negative,
# augmentation=True)
# patch_index_negative = extract_negative_patches_from_tumor_wsi(ops, pe, patch_index_negative, augmentation=True)
# extract_negative_patches_from_normal_wsi(ops, pe, patch_index_negative, augmentation=True)
# extract_positive_patches_from_tumor_wsi(ops, pe, patch_index_positive, augmentation=True)
if __name__ == '__main__':
extract_patches_augmented(WSIOps(), PatchExtractor())
# extract_patches(WSIOps(), PatchExtractor())