| """ |
| ================================================================================ |
| 脚本名称 (Script Name): test_deidentify_trial.py |
| 原本用途 (Original Purpose): |
| 几何掩模提取与脱敏算法单元回归测试套件。确保不同长宽比、不同黑边占比的眼底图像在裁切脱敏时视网膜有效组织不会被误切。 |
| 适用数据集 (Target Dataset): |
| 典型异常尺寸、强眩光、偏心光照的测试集样本。 |
| 作者与归属 (Author/Provenance): |
| 李思成 (Lisicheng), 浙江大学多模态眼科团队 |
| 输入要求 (Input): |
| 合成与极端边界用例图像 |
| 输出结果 (Output): |
| 单元测试断言与通过性报告 |
| 依赖环境 (Dependencies): |
| pytest, opencv-python, numpy |
| ================================================================================ |
| """ |
|
|
| import unittest |
| from argparse import Namespace |
| from pathlib import Path |
| import sys |
| import tarfile |
| from tempfile import TemporaryDirectory |
|
|
| import cv2 |
| import numpy as np |
|
|
| sys.path.insert(0, str(Path(__file__).resolve().parent)) |
|
|
| from deidentify_batch import metadata_for_row, process_one |
| from deidentify_trial import ( |
| blackout_frame, |
| blackout_top_bar, |
| crop_top_bar, |
| deidentify_fundus_circle, |
| deidentify_fundus_left_outside_circle, |
| parse_ocr_metadata, |
| ) |
|
|
|
|
| class DeidentifyTrialTest(unittest.TestCase): |
| def test_parse_ocr_metadata_keeps_only_non_identifier_fields(self): |
| meta = parse_ocr_metadata("张三 61岁 男 OD 2021/05/21 15:15") |
|
|
| self.assertEqual(meta, {"age": 61, "sex": "M", "eye": "OD"}) |
|
|
| def test_fundus_circle_mask_blacks_corner_and_keeps_retina(self): |
| img = np.zeros((160, 160, 3), dtype=np.uint8) |
| yy, xx = np.ogrid[:160, :160] |
| circle = (xx - 80) ** 2 + (yy - 80) ** 2 <= 58**2 |
| img[circle] = (90, 80, 70) |
| img[:16, :35] = (255, 255, 255) |
|
|
| out, ok, _ = deidentify_fundus_circle(img, radius_ratio=0.94, open_kernel=9) |
|
|
| self.assertTrue(ok) |
| self.assertTrue(np.all(out[4, 4] == 0)) |
| self.assertTrue(np.all(out[80, 80] == img[80, 80])) |
|
|
| def test_left_only_circle_mask_keeps_right_outside_circle(self): |
| img = np.zeros((160, 160, 3), dtype=np.uint8) |
| yy, xx = np.ogrid[:160, :160] |
| circle = (xx - 80) ** 2 + (yy - 80) ** 2 <= 58**2 |
| img[circle] = (90, 80, 70) |
| img[4, 4] = (255, 255, 255) |
| img[4, 150] = (123, 45, 67) |
|
|
| out, ok, _ = deidentify_fundus_left_outside_circle( |
| img, radius_ratio=0.985, left_ratio=0.55, open_kernel=9 |
| ) |
|
|
| self.assertTrue(ok) |
| self.assertTrue(np.all(out[4, 4] == 0)) |
| self.assertTrue(np.all(out[80, 80] == img[80, 80])) |
| self.assertTrue(np.array_equal(out[4, 150], img[4, 150])) |
|
|
| def test_blackout_top_bar_preserves_shape_and_masks_top_rows(self): |
| img = np.full((100, 80, 3), 128, dtype=np.uint8) |
|
|
| out = blackout_top_bar(img, ratio=0.12) |
|
|
| self.assertEqual(out.shape, img.shape) |
| self.assertTrue(np.all(out[:12] == 0)) |
| self.assertTrue(np.all(out[12:] == 128)) |
|
|
| def test_blackout_frame_masks_top_bottom_and_right_without_resizing(self): |
| img = np.full((100, 80, 3), 128, dtype=np.uint8) |
|
|
| out = blackout_frame(img, top=0.08, bottom=0.05, right=0.02) |
|
|
| self.assertEqual(out.shape, img.shape) |
| self.assertTrue(np.all(out[:8, :] == 0)) |
| self.assertTrue(np.all(out[95:, :] == 0)) |
| self.assertTrue(np.all(out[:, 78:] == 0)) |
| self.assertTrue(np.all(out[8:95, :78] == 128)) |
|
|
| def test_crop_top_bar_removes_requested_fraction(self): |
| img = np.arange(100 * 80 * 3, dtype=np.uint8).reshape(100, 80, 3) |
|
|
| out = crop_top_bar(img, ratio=0.12) |
|
|
| self.assertEqual(out.shape, (88, 80, 3)) |
| self.assertTrue(np.array_equal(out[0], img[12])) |
|
|
| def test_process_one_bscan_writes_opaque_jpeg_and_metadata(self): |
| with TemporaryDirectory() as tmp: |
| tmp_path = Path(tmp) |
| src = tmp_path / "source.bmp" |
| img = np.full((100, 80, 3), 128, dtype=np.uint8) |
| ok, encoded = cv2.imencode(".bmp", img) |
| self.assertTrue(ok) |
| encoded.tofile(str(src)) |
|
|
| args = Namespace( |
| out_root=tmp_path / "out", |
| bscan_top=0.10, |
| bscan_bottom=0.05, |
| bscan_right=0.02, |
| overwrite_images=False, |
| jpeg_quality=95, |
| ) |
| row = { |
| "image_id": "xiangya_bscan_00000001", |
| "cohort": "xiangya_bscan", |
| "file_path": str(src), |
| } |
|
|
| result = process_one(row, args, reader=None) |
|
|
| out_path = tmp_path / "out" / "images" / "xiangya_bscan" / "xiangya_bscan_00000001.jpg" |
| self.assertTrue(out_path.exists()) |
| self.assertEqual(result["deid_path"], str(out_path)) |
| self.assertEqual(result["deid_method"], "bscan_blackout_top10_bottom5_right2") |
| self.assertTrue(result["pii_masked"]) |
|
|
| def test_process_one_left_fundus_reads_tar_member(self): |
| with TemporaryDirectory() as tmp: |
| tmp_path = Path(tmp) |
| img = np.zeros((160, 160, 3), dtype=np.uint8) |
| yy, xx = np.ogrid[:160, :160] |
| circle = (xx - 80) ** 2 + (yy - 80) ** 2 <= 58**2 |
| img[circle] = (90, 80, 70) |
| img[4, 4] = (255, 255, 255) |
| ok, encoded = cv2.imencode(".png", img) |
| self.assertTrue(ok) |
|
|
| tar_path = tmp_path / "sample.tar" |
| png_path = tmp_path / "sample.png" |
| encoded.tofile(str(png_path)) |
| with tarfile.open(tar_path, "w") as tf: |
| tf.add(png_path, arcname="sample.png") |
|
|
| args = Namespace( |
| out_root=tmp_path / "out", |
| overwrite_images=False, |
| jpeg_quality=95, |
| fundus_threshold=25, |
| fundus_open_kernel=9, |
| left_fundus_radius_ratio=0.985, |
| left_fundus_ratio=0.55, |
| ) |
| row = { |
| "image_id": "tongren_fundus_00000001", |
| "cohort": "tongren_fundus", |
| "train_path": f"{tar_path}::sample.png", |
| "file_path": f"{tar_path}::sample.png", |
| "ocr_age": 61, |
| "ocr_sex": "F", |
| "ocr_eye": "OD", |
| } |
|
|
| result = process_one(row, args, reader=None) |
|
|
| self.assertTrue(Path(result["deid_path"]).exists()) |
| self.assertEqual(result["deid_method"], "fundus_left_outside_circle_mask_r0985_l055") |
| self.assertEqual(result["ocr_age"], 61) |
| self.assertEqual(result["ocr_sex"], "F") |
|
|
| def test_tongren_metadata_is_not_applied_to_fq_rows(self): |
| meta = {"1005653-1.png": {"age": 63, "sex": "F", "eye": "OD"}} |
|
|
| self.assertEqual( |
| metadata_for_row( |
| { |
| "cohort": "fq_rawfundus", |
| "rel_path": "1005653-1.png", |
| "train_path": "/nfs01/FQ_Datasets/data/rawFundus/1005653-1.png", |
| }, |
| meta, |
| ), |
| {}, |
| ) |
| self.assertEqual( |
| metadata_for_row( |
| { |
| "cohort": "tongren_fundus", |
| "rel_path": "1005653-1.png", |
| "train_path": "/data/team/lisicheng/Dataser/shards_tongren/fundus/a.tar::1005653-1.png", |
| }, |
| meta, |
| ), |
| {"age": 63, "sex": "F", "eye": "OD"}, |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
