mirror of
https://github.com/azaion/ai-training.git
synced 2026-04-22 08:56:35 +00:00
Oleksandr Bezdieniezhnykh
243b69656b
- Modified `.gitignore` to reflect the new path for test results. - Updated `docker-compose.test.yml` to mount the correct test results directory. - Adjusted `Dockerfile.test` to set the `PYTHONPATH` and ensure test results are saved in the updated location. - Added `boto3` and `netron` to `requirements-test.txt` to support new functionalities. - Updated `pytest.ini` to include the new `pythonpath` for test discovery. These changes streamline the testing process and ensure compatibility with the updated directory structure.
144 lines
4.6 KiB
Python
144 lines
4.6 KiB
Python
import random
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import shutil
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from pathlib import Path
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from types import SimpleNamespace
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import cv2
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import numpy as np
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import pytest
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from tests.conftest import apply_constants_patch
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def _patch_augmentation_paths(monkeypatch, base: Path):
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apply_constants_patch(monkeypatch, base)
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def _augment_annotation_with_total(monkeypatch):
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import augmentation as aug
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orig = aug.Augmentator.augment_annotation
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def wrapped(self, image_file):
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self.total_to_process = self.total_images_to_process
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return orig(self, image_file)
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monkeypatch.setattr(aug.Augmentator, "augment_annotation", wrapped)
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def _seed():
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random.seed(42)
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np.random.seed(42)
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@pytest.mark.resilience
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def test_rt_aug_01_corrupted_image_skipped(
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tmp_path, monkeypatch, fixture_images_dir, fixture_labels_dir
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):
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# Arrange
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_patch_augmentation_paths(monkeypatch, tmp_path)
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_augment_annotation_with_total(monkeypatch)
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_seed()
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import constants as c
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from augmentation import Augmentator
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img_dir = Path(c.config.data_images_dir)
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lbl_dir = Path(c.config.data_labels_dir)
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img_dir.mkdir(parents=True, exist_ok=True)
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lbl_dir.mkdir(parents=True, exist_ok=True)
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stem = sorted(fixture_images_dir.glob("*.jpg"))[0].stem
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shutil.copy2(fixture_images_dir / f"{stem}.jpg", img_dir / f"{stem}.jpg")
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shutil.copy2(fixture_labels_dir / f"{stem}.txt", lbl_dir / f"{stem}.txt")
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raw = (fixture_images_dir / f"{stem}.jpg").read_bytes()[:200]
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(img_dir / "corrupted_trunc.jpg").write_bytes(raw)
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# Act
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Augmentator().augment_annotations()
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# Assert
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proc_img = Path(c.config.processed_images_dir)
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assert len(list(proc_img.glob("*.jpg"))) == 8
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@pytest.mark.resilience
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def test_rt_aug_02_missing_label_no_crash(tmp_path, monkeypatch, fixture_images_dir):
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# Arrange
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_patch_augmentation_paths(monkeypatch, tmp_path)
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_augment_annotation_with_total(monkeypatch)
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import constants as c
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from augmentation import Augmentator
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img_dir = Path(c.config.data_images_dir)
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lbl_dir = Path(c.config.data_labels_dir)
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img_dir.mkdir(parents=True, exist_ok=True)
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lbl_dir.mkdir(parents=True, exist_ok=True)
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stem = "no_label_here"
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shutil.copy2(sorted(fixture_images_dir.glob("*.jpg"))[0], img_dir / f"{stem}.jpg")
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aug = Augmentator()
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aug.total_images_to_process = 1
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# Act
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aug.augment_annotation(SimpleNamespace(name=f"{stem}.jpg"))
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# Assert
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assert len(list(Path(c.config.processed_images_dir).glob("*.jpg"))) == 0
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@pytest.mark.resilience
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def test_rt_aug_03_narrow_bbox_fewer_or_eight_variants(
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tmp_path, monkeypatch, fixture_images_dir
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):
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# Arrange
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_patch_augmentation_paths(monkeypatch, tmp_path)
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_seed()
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from augmentation import Augmentator
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from dto.imageLabel import ImageLabel
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stem = "narrow_bbox"
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proc_img = Path(tmp_path) / "azaion" / "data-processed" / "images" / f"{stem}.jpg"
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proc_lbl = Path(tmp_path) / "azaion" / "data-processed" / "labels" / f"{stem}.txt"
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proc_img.parent.mkdir(parents=True, exist_ok=True)
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proc_lbl.parent.mkdir(parents=True, exist_ok=True)
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src_img = sorted(fixture_images_dir.glob("*.jpg"))[0]
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img = cv2.imdecode(np.fromfile(str(src_img), dtype=np.uint8), cv2.IMREAD_COLOR)
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aug = Augmentator()
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labels = [[0.5, 0.5, 0.0005, 0.0005, 0]]
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img_ann = ImageLabel(
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image_path=str(proc_img),
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image=img,
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labels_path=str(proc_lbl),
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labels=labels,
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)
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# Act
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out = aug.augment_inner(img_ann)
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# Assert
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assert 1 <= len(out) <= 8
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@pytest.mark.resource_limit
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def test_rl_aug_01_augment_inner_exactly_eight_outputs(
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tmp_path, monkeypatch, fixture_images_dir, fixture_labels_dir
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):
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# Arrange
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_patch_augmentation_paths(monkeypatch, tmp_path)
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_seed()
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from augmentation import Augmentator
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from dto.imageLabel import ImageLabel
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stem = sorted(fixture_images_dir.glob("*.jpg"))[0].stem
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img_path = fixture_images_dir / f"{stem}.jpg"
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lbl_path = fixture_labels_dir / f"{stem}.txt"
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img = cv2.imdecode(np.fromfile(str(img_path), dtype=np.uint8), cv2.IMREAD_COLOR)
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aug = Augmentator()
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labels = aug.read_labels(lbl_path)
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proc_img = Path(tmp_path) / "azaion" / "data-processed" / "images" / f"{stem}.jpg"
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proc_lbl = Path(tmp_path) / "azaion" / "data-processed" / "labels" / f"{stem}.txt"
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proc_img.parent.mkdir(parents=True, exist_ok=True)
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proc_lbl.parent.mkdir(parents=True, exist_ok=True)
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img_ann = ImageLabel(
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image_path=str(proc_img),
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image=img,
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labels_path=str(proc_lbl),
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labels=labels,
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)
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# Act
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out = aug.augment_inner(img_ann)
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# Assert
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assert len(out) == 8
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