[AZ-153] [AZ-155] [AZ-156] [AZ-158] Add augmentation, dataset formation, label validation, model split tests

Made-with: Cursor

tests/performance/test_dataset_perf.py

@@ -0,0 +1,103 @@
+import shutil
+import sys
+import time
+import types
+from os import path as osp
+from pathlib import Path
+
+import pytest
+
+import constants as c_mod
+
+
+def _stub_train_dependencies():
+    if getattr(_stub_train_dependencies, "_done", False):
+        return
+
+    def add_mod(name):
+        if name in sys.modules:
+            return sys.modules[name]
+        m = types.ModuleType(name)
+        sys.modules[name] = m
+        return m
+
+    ultra = add_mod("ultralytics")
+
+    class YOLO:
+        pass
+
+    ultra.YOLO = YOLO
+
+    def fake_client(*_a, **_k):
+        return types.SimpleNamespace(
+            upload_fileobj=lambda *_a, **_k: None,
+            download_file=lambda *_a, **_k: None,
+        )
+
+    boto = add_mod("boto3")
+    boto.client = fake_client
+    add_mod("netron")
+    add_mod("requests")
+    _stub_train_dependencies._done = True
+
+
+_stub_train_dependencies()
+
+
+def _prepare_form_dataset(
+    monkeypatch,
+    tmp_path,
+    constants_patch,
+    fixture_images_dir,
+    fixture_labels_dir,
+    count,
+    corrupt_stems,
+):
+    constants_patch(tmp_path)
+    import train
+
+    proc_img = Path(c_mod.processed_images_dir)
+    proc_lbl = Path(c_mod.processed_labels_dir)
+    proc_img.mkdir(parents=True, exist_ok=True)
+    proc_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_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")
+
+    today_ds = osp.join(c_mod.datasets_dir, train.today_folder)
+    monkeypatch.setattr(train, "today_dataset", today_ds)
+    monkeypatch.setattr(train, "processed_images_dir", c_mod.processed_images_dir)
+    monkeypatch.setattr(train, "processed_labels_dir", c_mod.processed_labels_dir)
+    monkeypatch.setattr(train, "corrupted_images_dir", c_mod.corrupted_images_dir)
+    monkeypatch.setattr(train, "corrupted_labels_dir", c_mod.corrupted_labels_dir)
+    monkeypatch.setattr(train, "datasets_dir", c_mod.datasets_dir)
+    return train
+
+
+@pytest.mark.performance
+def test_pt_dsf_01_dataset_formation_under_thirty_seconds(
+    monkeypatch,
+    tmp_path,
+    constants_patch,
+    fixture_images_dir,
+    fixture_labels_dir,
+):
+    train = _prepare_form_dataset(
+        monkeypatch,
+        tmp_path,
+        constants_patch,
+        fixture_images_dir,
+        fixture_labels_dir,
+        100,
+        set(),
+    )
+    t0 = time.perf_counter()
+    train.form_dataset()
+    elapsed = time.perf_counter() - t0
+    assert elapsed <= 30.0