""" Copyright 2021, Dana-Farber Cancer Institute and Weill Cornell Medicine License: GNU GPL 2.0 """ import urllib import zipfile import cv2 import numpy as np import pytest from pathml.datasets import PanNukeDataModule from pathml.datasets.pannuke import PanNukeDataset from pathml.datasets.utils import pannuke_multiclass_mask_to_nucleus_mask def create_fake_pannuke_data(target_dir, n_fold=16): """ create some fake images and masks in target_dir/images and target_dir/masks Args: target_dir (pathlib.Path): directory where to save the images and masks. 'images' and 'masks' subdirectories will be created here. n_fold (int): number of images and masks per fold """ folds = [1, 2, 3] tissue_types = ["breast", "colon", "head-neck"] imdir = target_dir / "images" maskdir = target_dir / "masks" imdir.mkdir() maskdir.mkdir() for fold_ix in folds: for i in range(n_fold): im = np.random.randint(low=2, high=254, size=(256, 256, 3), dtype=np.uint8) mask = np.random.randint(low=0, high=10, size=(6, 256, 256), dtype=np.uint8) tissue_type = np.random.choice(tissue_types) im_fname = imdir / f"fold{fold_ix}_{i}_{tissue_type}.png" im_fname = str(im_fname.resolve()) mask_fname = maskdir / f"fold{fold_ix}_{i}_{tissue_type}.npy" mask_fname = str(mask_fname.resolve()) cv2.imwrite(im_fname, im) np.save(mask_fname, mask) @pytest.mark.parametrize("fold", [1, 2, 3, None]) @pytest.mark.parametrize("nucleus_type_labels", [True, False]) def test_pannuke_dataset_sizes(tmp_path, fold, nucleus_type_labels): n_fold = 16 create_fake_pannuke_data(tmp_path, n_fold=n_fold) pannuke_dataset = PanNukeDataset( data_dir=tmp_path, fold_ix=fold, nucleus_type_labels=nucleus_type_labels ) # check size of dataset if fold in [1, 2, 3]: assert len(pannuke_dataset) == n_fold else: assert len(pannuke_dataset) == 3 * n_fold # check shapes of individual elements im, mask, lab = pannuke_dataset[0] assert im.shape == (3, 256, 256) if nucleus_type_labels: assert mask.shape == (6, 256, 256) else: assert mask.shape == (256, 256) def create_fake_pannuke_data_raw(target_dir, fold_size=16): """ Create some fake raw data that mimics file structure of what is downloaded from PanNuke website: https://warwick.ac.uk/fac/sci/dcs/research/tia/data/pannuke/ Args: target_dir (pathlib.Path): directory where to save the data. fold_size (int): number of images and masks per fold """ folds = [1, 2, 3] tissue_types = ["breast", "colon", "head-neck"] for fold_ix in folds: # create the directories images_dir = target_dir / f"Fold {fold_ix}" / "images" / f"fold{fold_ix}" masks_dir = target_dir / f"Fold {fold_ix}" / "masks" / f"fold{fold_ix}" images_dir.mkdir(parents=True) masks_dir.mkdir(parents=True) # create the fake data types_fold = np.random.choice(tissue_types, size=fold_size) masks = np.random.randint(low=0, high=10, size=(fold_size, 256, 256, 6)) ims = np.random.randint(low=0, high=254, size=(fold_size, 256, 256, 3)) # write the data np.save(file=str(images_dir / "images.npy"), arr=ims) np.save(file=str(images_dir / "types.npy"), arr=types_fold) np.save(file=str(masks_dir / "masks.npy"), arr=masks) def test_process_downloaded_pannuke(tmp_path): """Test the post-processing of the pannuke raw data""" # make fake data fold_size = 16 create_fake_pannuke_data_raw(tmp_path, fold_size=fold_size) # process the fake data PanNukeDataModule._process_downloaded_pannuke(tmp_path) # check everything imdir = tmp_path / "images" maskdir = tmp_path / "masks" assert imdir.is_dir() assert maskdir.is_dir() assert len(list(imdir.glob("*"))) == 3 * fold_size assert len(list(maskdir.glob("*"))) == 3 * fold_size for fold_ix in [1, 2, 3]: assert len(list(imdir.glob(f"fold{fold_ix}*"))) == fold_size assert len(list(maskdir.glob(f"fold{fold_ix}*"))) == fold_size @pytest.mark.parametrize("raw_data", [True, False]) @pytest.mark.parametrize("hovernet_preprocess", [True, False]) @pytest.mark.parametrize("split", [1, 2, 3, None]) @pytest.mark.parametrize("nucleus_type_labels", [True, False]) def test_pannuke_datamodule( tmp_path, split, nucleus_type_labels, hovernet_preprocess, raw_data ): # make fake data # if raw_data, then also test processing step fold_size = 8 if raw_data: create_fake_pannuke_data_raw(tmp_path, fold_size=fold_size) # process the fake data PanNukeDataModule._process_downloaded_pannuke(tmp_path) else: create_fake_pannuke_data(tmp_path, n_fold=fold_size) batch_size = 4 pannuke = PanNukeDataModule( data_dir=tmp_path, nucleus_type_labels=nucleus_type_labels, split=split, download=False, transforms=None, batch_size=batch_size, hovernet_preprocess=hovernet_preprocess, ) train = pannuke.train_dataloader valid = pannuke.valid_dataloader test = pannuke.test_dataloader for loader in [train, test, valid]: # make sure everything is correct dimensions if hovernet_preprocess: im, mask, hv, tissue_types = next(iter(loader)) assert hv.shape == (batch_size, 2, 256, 256) else: im, mask, tissue_types = next(iter(loader)) assert im.shape == (batch_size, 3, 256, 256) if nucleus_type_labels: assert mask.shape == (batch_size, 6, 256, 256) else: assert mask.shape == (batch_size, 256, 256) assert len(tissue_types) == batch_size and all( [isinstance(t, str) for t in tissue_types] ) def test_clean_up_download_pannuke(tmp_path): # first create the files and dirs to delete for fold_ix in [1, 2, 3]: with zipfile.ZipFile(tmp_path / f"fold_{fold_ix}.zip", "w") as myzip: myzip.writestr("fake_pannuke_data.txt", "NYE 2020 - happy new year!") downloaded_dir = tmp_path / f"Fold {fold_ix}" downloaded_dir.mkdir() # add some data inside the dirs (test for issue #53) data = np.random.randint(low=0, high=10, size=(8, 256, 256, 6)) np.save(file=str(downloaded_dir / "data.npy"), arr=data) # now call cleanup PanNukeDataModule._clean_up_download_pannuke(tmp_path) # now make sure that the files/dirs were deleted for fold_ix in [1, 2, 3]: zfile = tmp_path / f"fold_{fold_ix}.zip" downloaded_dir = tmp_path / f"Fold {fold_ix}" assert not zfile.exists() assert not downloaded_dir.exists() def check_pannuke_data_urls(): # make sure that the urls for the pannuke data are still valid! for fold_ix in [1, 2, 3]: url = f"https://warwick.ac.uk/fac/sci/dcs/research/tia/data/pannuke/fold_{fold_ix}.zip" r = urllib.request.urlopen(url) # HTTP status code 200 means "OK" assert r.getcode() == 200 def check_wrong_path_download_false_fails(): with pytest.raises(AssertionError): PanNukeDataModule(data_dir="wrong/path/to/pannuke", download=False) def test_pannuke_multiclass_mask_to_nucleus_mask(): mask = np.random.randint(low=0, high=10, size=(6, 256, 256), dtype=np.uint8) mask_1c = pannuke_multiclass_mask_to_nucleus_mask(mask) assert mask_1c.shape == (256, 256) # TODO add tests for _download_pannuke()