Refactor configuration and update test structure for improved clarity

- Updated `.gitignore` to remove committed test fixture data exclusions. - Increased batch size in `config.test.yaml` from 4 to 128 for training. - Simplified directory structure in `config.yaml` by removing unnecessary data paths. - Adjusted paths in `augmentation.py`, `dataset-visualiser.py`, and `exports.py` to align with the new configuration structure. - Enhanced `annotation_queue_handler.py` to utilize the updated configuration for directory management. - Added CSV logging of test results in `conftest.py` for better test reporting. These changes streamline the configuration management and enhance the testing framework, ensuring better organization and clarity in the project.
2026-04-22 07:06:36 +00:00 · 2026-03-28 07:32:40 +02:00
parent a47fa135de
commit 18b88ba9bf
90 changed files with 140 additions and 141 deletions
@@ -1,3 +1,4 @@
+import csv
 import shutil
 from pathlib import Path

@@ -14,6 +15,34 @@ _CONFIG_TEST = _PROJECT_ROOT / "config.test.yaml"

 collect_ignore = ["security_test.py", "imagelabel_visualize_test.py"]

+_test_results = []
+
+
+@pytest.hookimpl(tryfirst=True, hookwrapper=True)
+def pytest_runtest_makereport(item, call):
+    outcome = yield
+    report = outcome.get_result()
+    if report.when == "call" or (report.when == "setup" and report.skipped):
+        _test_results.append({
+            "module": item.nodeid.rsplit("::", 1)[0],
+            "name": item.name,
+            "result": report.outcome.upper(),
+            "duration": round(report.duration, 3),
+        })
+
+
+def pytest_sessionfinish(session, exitstatus):
+    if not _test_results:
+        return
+    results_dir = Path(__file__).resolve().parent / "test-results"
+    results_dir.mkdir(exist_ok=True)
+
+    with open(results_dir / "test-results.csv", "w", newline="", encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow(["module", "test", "result", "duration_s"])
+        for r in _test_results:
+            writer.writerow([r["module"], r["name"], r["result"], f"{r['duration']:.3f}"])
+

 def apply_constants_patch(monkeypatch, base: Path):
    import constants as c
@@ -20,16 +20,16 @@ def _prepare_form_dataset(
    constants_patch(tmp_path)
    import train

-    proc_img = Path(c_mod.config.processed_images_dir)
-    proc_lbl = Path(c_mod.config.processed_labels_dir)
-    proc_img.mkdir(parents=True, exist_ok=True)
-    proc_lbl.mkdir(parents=True, exist_ok=True)
+    data_img = Path(c_mod.config.images_dir)
+    data_lbl = Path(c_mod.config.labels_dir)
+    data_img.mkdir(parents=True, exist_ok=True)
+    data_lbl.mkdir(parents=True, exist_ok=True)

    imgs = sorted(fixture_images_dir.glob("*.jpg"))[:count]
    for p in imgs:
        stem = p.stem
-        shutil.copy2(fixture_images_dir / f"{stem}.jpg", proc_img / f"{stem}.jpg")
-        dst = proc_lbl / f"{stem}.txt"
+        shutil.copy2(fixture_images_dir / f"{stem}.jpg", data_img / f"{stem}.jpg")
+        dst = data_lbl / f"{stem}.txt"
        shutil.copy2(fixture_labels_dir / f"{stem}.txt", dst)
        if stem in corrupt_stems:
            dst.write_text("0 1.5 0.5 0.1 0.1\n", encoding="utf-8")
@@ -1 +0,0 @@
-0 0.63516 0.76054 0.05480 0.09305
@@ -1 +0,0 @@
-0 0.61853 0.77915 0.05973 0.09305
@@ -1 +0,0 @@
-0 0.47200 0.78007 0.26215 0.42338
@@ -1,2 +0,0 @@
-0 0.76062 0.31074 0.08738 0.13238
-0 0.79600 0.20352 0.04985 0.08424
@@ -1,6 +0,0 @@
-6 0.52646 0.69638 0.04738 0.18161
-6 0.56554 0.69856 0.03077 0.16848
-6 0.59908 0.69311 0.03754 0.17263
-6 0.70000 0.74293 0.04738 0.17176
-6 0.77046 0.69638 0.03077 0.14441
-6 0.73538 0.70190 0.03077 0.14660
@@ -1,4 +0,0 @@
-6 0.63569 0.46827 0.04185 0.13675
-6 0.68492 0.38403 0.04800 0.13019
-6 0.61569 0.36161 0.03877 0.10065
-6 0.56708 0.44147 0.04985 0.12253
@@ -1 +0,0 @@
-3 0.74738 0.58588 0.33415 0.49450
@@ -1 +0,0 @@
-0 0.91200 0.50492 0.09846 0.08971
@@ -1 +0,0 @@
-0 0.87846 0.50930 0.09785 0.07658
@@ -1 +0,0 @@
-2 0.53169 0.44475 0.06523 0.12691
@@ -1 +0,0 @@
-2 0.51323 0.45679 0.08369 0.08752
@@ -1 +0,0 @@
-0 0.90154 0.37309 0.08246 0.10831
@@ -1,4 +0,0 @@
-6 0.35723 0.48851 0.03015 0.12253
-6 0.21415 0.44147 0.02954 0.11597
-6 0.24277 0.44147 0.02769 0.11597
-6 0.28892 0.44530 0.02769 0.08205
@@ -1 +0,0 @@
-3 0.24338 0.33097 0.16308 0.21443
@@ -1 +0,0 @@
-3 0.53200 0.18055 0.07815 0.08862
@@ -1 +0,0 @@
-1 0.63538 0.20571 0.05354 0.11050
@@ -1 +0,0 @@
-3 0.70092 0.15046 0.04431 0.06564
@@ -1 +0,0 @@
-1 0.28431 0.81398 0.12677 0.33805
@@ -1,2 +0,0 @@
-0 0.33108 0.75600 0.23262 0.35556
-6 0.10862 0.51641 0.03385 0.09080
@@ -1 +0,0 @@
-0 0.41138 0.64113 0.29108 0.21552
@@ -1 +0,0 @@
-0 0.47200 0.78007 0.26215 0.42338
@@ -1,2 +0,0 @@
-0 0.76062 0.31074 0.08738 0.13238
-0 0.79600 0.20352 0.04985 0.08424
@@ -1,6 +0,0 @@
-6 0.52646 0.69638 0.04738 0.18161
-6 0.56554 0.69856 0.03077 0.16848
-6 0.59908 0.69311 0.03754 0.17263
-6 0.70000 0.74293 0.04738 0.17176
-6 0.77046 0.69638 0.03077 0.14441
-6 0.73538 0.70190 0.03077 0.14660
@@ -1,4 +0,0 @@
-6 0.63569 0.46827 0.04185 0.13675
-6 0.68492 0.38403 0.04800 0.13019
-6 0.61569 0.36161 0.03877 0.10065
-6 0.56708 0.44147 0.04985 0.12253
@@ -1 +0,0 @@
-3 0.74738 0.58588 0.33415 0.49450
@@ -1 +0,0 @@
-0 0.91200 0.50492 0.09846 0.08971
@@ -1 +0,0 @@
-0 0.87846 0.50930 0.09785 0.07658
@@ -1 +0,0 @@
-2 0.53169 0.44475 0.06523 0.12691
@@ -1 +0,0 @@
-2 0.51323 0.45679 0.08369 0.08752
@@ -1 +0,0 @@
-0 0.90154 0.37309 0.08246 0.10831
@@ -1,4 +0,0 @@
-6 0.35723 0.48851 0.03015 0.12253
-6 0.21415 0.44147 0.02954 0.11597
-6 0.24277 0.44147 0.02769 0.11597
-6 0.28892 0.44530 0.02769 0.08205
@@ -1 +0,0 @@
-3 0.24338 0.33097 0.16308 0.21443
@@ -1 +0,0 @@
-3 0.53200 0.18055 0.07815 0.08862
@@ -1 +0,0 @@
-1 0.63538 0.20571 0.05354 0.11050
@@ -1 +0,0 @@
-3 0.70092 0.15046 0.04431 0.06564
@@ -1 +0,0 @@
-1 0.28431 0.81398 0.12677 0.33805
@@ -1,2 +0,0 @@
-0 0.33108 0.75600 0.23262 0.35556
-6 0.10862 0.51641 0.03385 0.09080
@@ -1 +0,0 @@
-0 0.41138 0.64113 0.29108 0.21552
@@ -19,16 +19,16 @@ def _prepare_form_dataset(
    constants_patch(tmp_path)
    import train

-    proc_img = Path(c_mod.config.processed_images_dir)
-    proc_lbl = Path(c_mod.config.processed_labels_dir)
-    proc_img.mkdir(parents=True, exist_ok=True)
-    proc_lbl.mkdir(parents=True, exist_ok=True)
+    data_img = Path(c_mod.config.images_dir)
+    data_lbl = Path(c_mod.config.labels_dir)
+    data_img.mkdir(parents=True, exist_ok=True)
+    data_lbl.mkdir(parents=True, exist_ok=True)

    imgs = sorted(fixture_images_dir.glob("*.jpg"))[:count]
    for p in imgs:
        stem = p.stem
-        shutil.copy2(fixture_images_dir / f"{stem}.jpg", proc_img / f"{stem}.jpg")
-        dst = proc_lbl / f"{stem}.txt"
+        shutil.copy2(fixture_images_dir / f"{stem}.jpg", data_img / f"{stem}.jpg")
+        dst = data_lbl / f"{stem}.txt"
        shutil.copy2(fixture_labels_dir / f"{stem}.txt", dst)
        if stem in corrupt_stems:
            dst.write_text("0 1.5 0.5 0.1 0.1\n", encoding="utf-8")
@@ -156,7 +156,7 @@ def test_bt_dsf_04_corrupted_labels_quarantined(


@pytest.mark.resilience
-def test_rt_dsf_01_empty_processed_no_crash(
+def test_rt_dsf_01_empty_data_no_crash(
    monkeypatch,
    tmp_path,
    constants_patch,
@@ -1,3 +1,4 @@
+import os
 import shutil
 from os import path
 from pathlib import Path
@@ -13,15 +14,42 @@ _TESTS_DIR = Path(__file__).resolve().parent
 _TEST_ROOT = _TESTS_DIR / "root"
 _DATASET_IMAGES = _TEST_ROOT / "data" / "images"
 _CONFIG_TEST = _TESTS_DIR.parent / "config.test.yaml"
+_SOURCE_DATASET = _TESTS_DIR.parent / "_docs" / "00_problem" / "input_data" / "dataset"
+
+
+def _hardlink_tree(src_dir: Path, dst_dir: Path):
+    dst_dir.mkdir(parents=True, exist_ok=True)
+    for f in src_dir.iterdir():
+        if f.is_file():
+            target = dst_dir / f.name
+            if not target.exists():
+                os.link(f, target)


@pytest.fixture(scope="module")
 def e2e_result():
+    # Arrange
+    src_images = _SOURCE_DATASET / "images"
+    src_labels = _SOURCE_DATASET / "labels"
+    if not src_images.is_dir() or not src_labels.is_dir():
+        pytest.skip("source dataset not found")
+
    old_config = c.config
    c.config = c.Config.from_yaml(str(_CONFIG_TEST), root=str(_TEST_ROOT))

+    dst_images = Path(c.config.images_dir)
+    dst_labels = Path(c.config.labels_dir)
+    for d in (dst_images, dst_labels, c.config.datasets_dir, c.config.models_dir, c.config.corrupted_dir):
+        shutil.rmtree(str(d), ignore_errors=True)
+
+    _hardlink_tree(src_images, dst_images)
+    _hardlink_tree(src_labels, dst_labels)
+
+    linked_count = len(list(dst_images.glob("*.jpg")))
+
    Path(c.config.models_dir).mkdir(parents=True, exist_ok=True)

+    # Act
    train_mod.train_dataset()

    exports_mod.export_onnx(c.config.current_pt_model)
@@ -31,8 +59,11 @@ def e2e_result():

    yield {
        "today_dataset": today_ds,
+        "linked_count": linked_count,
    }

+    shutil.rmtree(str(dst_images), ignore_errors=True)
+    shutil.rmtree(str(dst_labels), ignore_errors=True)
    shutil.rmtree(c.config.datasets_dir, ignore_errors=True)
    shutil.rmtree(c.config.models_dir, ignore_errors=True)
    shutil.rmtree(c.config.corrupted_dir, ignore_errors=True)
@@ -42,6 +73,7 @@ def e2e_result():
@pytest.mark.e2e
 class TestTrainingPipeline:
    def test_dataset_formed(self, e2e_result):
+        # Assert
        base = Path(e2e_result["today_dataset"])
        for split in ("train", "valid", "test"):
            assert (base / split / "images").is_dir()
@@ -50,7 +82,7 @@ class TestTrainingPipeline:
            len(list((base / s / "images").glob("*.jpg")))
            for s in ("train", "valid", "test")
        )
-        assert total == 20
+        assert 0 < total <= e2e_result["linked_count"]

    def test_data_yaml_created(self, e2e_result):
        yaml_path = Path(e2e_result["today_dataset"]) / "data.yaml"