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README.md

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+---
+configs:
+  - config_name: close_ended
+    data_files:
+      - split: val
+        path: close_ended.json
+  - config_name: open_ended
+    data_files:
+      - split: val
+        path: open_ended.json
+license: mit
+task_categories:
+  - visual-question-answering
+language:
+  - en
+tags:
+  - spatial-reasoning
+  - object-location
+  - direction
+---
+
+# Object Location 4-Class (Subset 1 of 5)
+
+A visual question answering dataset for evaluating spatial reasoning — specifically, identifying the location of an object (Up / Down / Left / Right) from the viewer's perspective.
+
+## Dataset Configurations
+
+### `close_ended`
+Multiple-choice format with 4 fixed options (A: Up, B: Down, C: Left, D: Right).
+
+### `open_ended`
+Free-form answer format. The model is expected to respond with one of: Up, Down, Left, Right.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Close-ended (multiple choice)
+ds_close = load_dataset("YOUR_HF_ID/object_location_4class", name="close_ended", split="val")
+
+# Open-ended (free-form)
+ds_open = load_dataset("YOUR_HF_ID/object_location_4class", name="open_ended", split="val")
+```
+
+## Data Fields
+
+### Close-ended
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | int | Sample index |
+| `image` | string | Image filename (e.g., `rectangle_yellow_123.png`) |
+| `question` | string | Question text |
+| `options` | list[string] | `["Up", "Down", "Left", "Right"]` |
+| `answer` | string | Correct option letter (`A`/`B`/`C`/`D`) |
+| `answer_text` | string | Correct answer in text (`Up`/`Down`/`Left`/`Right`) |
+| `category` | string | Ground truth direction folder (`up`/`down`/`left`/`right`) |
+
+### Open-ended
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | int | Sample index |
+| `image` | string | Image filename (e.g., `rectangle_yellow_123.png`) |
+| `question` | string | Question text |
+| `answer` | string | Correct answer (`Up`/`Down`/`Left`/`Right`) |
+| `category` | string | Ground truth direction folder (`up`/`down`/`left`/`right`) |
+
+## Notes
+
+- Images are **not** included in this repository. They should be stored locally and loaded via the `category` and `image` fields to reconstruct the full path:
+  ```
+  {DATA_ROOT}/{category}/{image}
+  ```

making_json.py

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+"""
+로컬 이미지 디렉토리에서 lmms-eval용 JSON 데이터셋 2종 생성
+- close_ended.json : 4지선다 (A/B/C/D)
+- open_ended.json  : 자유 응답 (Up/Down/Left/Right)
+"""
+
+import os
+import json
+import glob
+
+# ============================================================
+# 설정
+# ============================================================
+DATA_ROOT = "/data/dataset/vlm_direction/object_location_4_class_subset_1of5/val"
+OUTPUT_DIR = "./"
+
+# 폴더명 → 영어 레이블 매핑
+LABEL_MAP = {
+    "up":    "Up",
+    "down":  "Down",
+    "left":  "Left",
+    "right": "Right",
+}
+
+# Close-ended 선택지 (고정 순서)
+OPTIONS = ["Up", "Down", "Left", "Right"]
+OPTION_LETTERS = ["A", "B", "C", "D"]
+
+# ============================================================
+# 데이터 수집
+# ============================================================
+close_ended_data = []
+open_ended_data = []
+
+idx = 0
+for folder_name, eng_label in LABEL_MAP.items():
+    folder_path = os.path.join(DATA_ROOT, folder_name)
+    if not os.path.isdir(folder_path):
+        print(f"[WARNING] 폴더 없음: {folder_path}")
+        continue
+
+    image_files = sorted(
+        glob.glob(os.path.join(folder_path, "*.png"))
+        + glob.glob(os.path.join(folder_path, "*.jpg"))
+        + glob.glob(os.path.join(folder_path, "*.jpeg"))
+    )
+    print(f"[INFO] {folder_name}: {len(image_files)} images found")
+
+    for img_path in image_files:
+        # abs_path = os.path.abspath(img_path)
+        filename = os.path.basename(img_path)
+
+        # 정답 옵션 letter (A/B/C/D)
+        answer_idx = OPTIONS.index(eng_label)
+        answer_letter = OPTION_LETTERS[answer_idx]
+
+        # --------------------------------------------------
+        # 1) Close-ended (4지선다)
+        # --------------------------------------------------
+        close_ended_data.append({
+            "id": idx,
+            "image": filename,
+            "question": "From the viewer's perspective, where is the object located in the image?",
+            "options": OPTIONS,              # ["Up", "Down", "Left", "Right"]
+            "answer": answer_letter,         # "A" / "B" / "C" / "D"
+            "answer_text": eng_label,        # "Up" / "Down" / "Left" / "Right"
+            "category": folder_name,
+        })
+
+        # --------------------------------------------------
+        # 2) Open-ended (자유 응답)
+        # --------------------------------------------------
+        open_ended_data.append({
+            "id": idx,
+            "image": filename,
+            "question": "From the viewer's perspective, where is the object located in the image? Answer with one of: Up, Down, Left, Right.",
+            "answer": eng_label,             # "Up" / "Down" / "Left" / "Right"
+            "category": folder_name,
+        })
+
+        idx += 1
+
+# ============================================================
+# JSON 저장
+# ============================================================
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+close_path = os.path.join(OUTPUT_DIR, "close_ended.json")
+open_path  = os.path.join(OUTPUT_DIR, "open_ended.json")
+
+with open(close_path, "w", encoding="utf-8") as f:
+    json.dump(close_ended_data, f, ensure_ascii=False, indent=2)
+
+with open(open_path, "w", encoding="utf-8") as f:
+    json.dump(open_ended_data, f, ensure_ascii=False, indent=2)
+
+print(f"\n{'='*60}")
+print(f"Total {idx} samples processed")
+print(f"Close-ended → {close_path} ({len(close_ended_data)} samples)")
+print(f"Open-ended  → {open_path} ({len(open_ended_data)} samples)")
+print(f"{'='*60}")
+
+# 샘플 출력
+print("\n[Sample] Close-ended:")
+print(json.dumps(close_ended_data[0], ensure_ascii=False, indent=2))
+print("\n[Sample] Open-ended:")
+print(json.dumps(open_ended_data[0], ensure_ascii=False, indent=2))