add

tools/gen_config.py

@@ -0,0 +1,28 @@
+import os, json, tensorflow as tf
+
+# 1) baca label dari class_indices.json (prioritas)
+labels = ["Heart","Oblong","Oval","Round","Square"]
+ci_path = os.path.join("models", "class_indices.json")
+if os.path.exists(ci_path):
+    with open(ci_path, "r") as f:
+        ci = json.load(f)  # {"Heart":0,...}
+    labels = [k for k,_ in sorted(ci.items(), key=lambda kv: kv[1])]
+
+# 2) ambil ukuran input langsung dari model.keras
+m = tf.keras.models.load_model(os.path.join("models","model.keras"), compile=False)
+h, w = m.input_shape[1], m.input_shape[2]
+assert h == w and h is not None, f"Input shape aneh: {m.input_shape}"
+img_size = int(h)
+
+# 3) tulis config.json
+cfg = {
+    "architectures": ["EfficientNetB4"],
+    "image_size": img_size,
+    "num_labels": len(labels),
+    "id2label": {str(i): lbl for i, lbl in enumerate(labels)},
+    "label2id": {lbl: i for i, lbl in enumerate(labels)},
+}
+with open("config.json", "w") as f:
+    json.dump(cfg, f, indent=2)
+
+print("Wrote config.json with image_size =", img_size, "and labels =", labels)