ADD: Manual Classifier to create training data

classifier-training/manual-classifier.py

@@ -0,0 +1,34 @@
+# quick_labeler.py
+import random
+import shutil, os
+from pathlib import Path
+from PIL import Image
+import matplotlib.pyplot as plt
+
+SOURCE = Path("alle_meine_fotos/")
+images = list(SOURCE.glob("**/*.jpg")) + list(SOURCE.glob("**/*.png"))
+
+
+DIRS = [
+    "dataset/train/wallpaper", "dataset/train/no_wallpaper",
+    "dataset/val/wallpaper",   "dataset/val/no_wallpaper",
+]
+for d in DIRS:
+    Path(d).mkdir(parents=True, exist_ok=True)
+
+for img_path in images:
+    img = Image.open(img_path)
+    plt.imshow(img)
+    plt.title(img_path.name)
+    plt.axis("off")
+    plt.show(block=False)
+
+    label = input("Wallpaper? (y/n/q): ").strip().lower()
+    plt.close()
+
+    if label == "q":
+        break
+    elif label in ("y", "n"):
+        folder = "wallpaper" if label == "y" else "no_wallpaper"
+        split  = "train" if random.random() < 0.8 else "val"
+        shutil.copy(img_path, f"dataset/{split}/{folder}/{img_path.name}")