simplify module3 venue workflow

module3/simple_prepare_dataset.py

@@ -5,18 +5,24 @@ from pathlib import Path
 
 
 HERE = Path(__file__).resolve().parent
-SOURCE = HERE / "dataset/raw"
+SOURCE = HERE / "dataset/label-studio"
+IMAGES = SOURCE / "images"
 LABELS = SOURCE / "labels"
 OUTPUT = HERE / "training_new"
 IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".bmp", ".webp"}
 
 
 def main():
-    images = sorted(path for path in SOURCE.iterdir() if path.suffix.lower() in IMAGE_EXTENSIONS)
+    if not IMAGES.is_dir():
+        raise SystemExit(f"Нет каталога {IMAGES}")
+    images = sorted(path for path in IMAGES.iterdir() if path.suffix.lower() in IMAGE_EXTENSIONS)
     if not images:
-        raise SystemExit(f"Нет кадров в {SOURCE}")
+        raise SystemExit(f"Нет кадров в {IMAGES}")
     if not LABELS.is_dir():
         raise SystemExit(f"Сначала экспортируйте YOLO-разметку в {LABELS}")
+    classes_file = SOURCE / "classes.txt"
+    if not classes_file.is_file():
+        raise SystemExit(f"Нет {classes_file}")
 
     random.Random(42).shuffle(images)
     test_count = max(1, round(len(images) * 0.1)) if len(images) >= 3 else 0
@@ -44,7 +50,7 @@ def main():
             else:
                 destination.touch()
 
-    classes = (HERE / "dataset/classes.txt").read_text(encoding="utf-8").splitlines()
+    classes = classes_file.read_text(encoding="utf-8").splitlines()
     names = "\n".join(f"  {number}: {name}" for number, name in enumerate(classes))
     (OUTPUT / "data.yaml").write_text(
         f"path: {OUTPUT}\ntrain: train/images\nval: valid/images\ntest: test/images\n\nnames:\n{names}\n",