makejson.py

import os
import json
import glob
import random

# ============================================================
# 설정
# ============================================================
import os
import json
import glob
import random
from collections import defaultdict

# ============================================================
# 설정
# ============================================================
DATA_ROOT = "/data/dataset/vlm_direction/direction_benchmarks/E2E_real_object"
OUTPUT_DIR = "./"

DIRECTION_CLASSES = ["up", "down", "left", "right"]
DIRECTION_OPTIONS = ["Up", "Down", "Left", "Right"]
DIR_TO_LETTER = {"up": "A", "down": "B", "left": "C", "right": "D"}
DIR_TO_LABEL = {"up": "Up", "down": "Down", "left": "Left", "right": "Right"}

random.seed(42)

# ============================================================
# 데이터 수집
# ============================================================
all_samples = []
all_objects = set()

for cls in DIRECTION_CLASSES:
    cls_dir = os.path.join(DATA_ROOT, cls)
    if not os.path.isdir(cls_dir):
        print(f"[WARN] Directory not found: {cls_dir}")
        continue

    videos = sorted(glob.glob(os.path.join(cls_dir, "*.mp4")))
    print(f"{cls}: {len(videos)} videos")

    # 고유명사 → 일반명사 매핑
    OBJ_NAME_MAP = {
        "sophia": "person",
    }

    for video_path in videos:
        filename = os.path.basename(video_path)
        raw_name = os.path.splitext(filename)[0]  # car.mp4 → car
        obj_name = OBJ_NAME_MAP.get(raw_name, raw_name)  # sophia → person
        video_rel = f"{cls}/{filename}"

        all_samples.append({
            "video": video_rel,
            "category": cls,
            "object": obj_name,
        })
        all_objects.add(obj_name)

all_objects = sorted(list(all_objects))
print(f"\nTotal: {len(all_samples)} samples, {len(all_objects)} unique objects")
print(f"Objects: {all_objects}")


# ============================================================
# JSON 생성 함수
# ============================================================
def make_direction_only(samples):
    """조건1: 기본 - object 언급 없이 방향만"""
    question = "In which direction is the object moving in this video?"
    close, open_ = [], []

    for s in samples:
        close.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "options": DIRECTION_OPTIONS,
            "answer": DIR_TO_LETTER[s["category"]],
        })
        open_.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "answer": DIR_TO_LABEL[s["category"]],
        })
    return close, open_


def make_direction_obj_in_q(samples):
    """조건2: 질문에 object 이름 포함"""
    close, open_ = [], []

    for s in samples:
        obj = s["object"]
        question = f"In which direction is the {obj} moving in this video?"
        close.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "options": DIRECTION_OPTIONS,
            "answer": DIR_TO_LETTER[s["category"]],
        })
        open_.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "answer": DIR_TO_LABEL[s["category"]],
        })
    return close, open_


def make_direction_obj_in_a(samples):
    """조건3: 답변에 object 이름 포함"""
    question = "In which direction is the object moving in this video?"
    close, open_ = [], []

    for s in samples:
        obj = s["object"]
        direction = DIR_TO_LABEL[s["category"]]

        # close-ended: 선택지에 object 포함
        options = [f"The {obj} is moving {d.lower()}" for d in DIRECTION_OPTIONS]
        answer_idx = DIRECTION_CLASSES.index(s["category"])
        answer_letter = chr(ord("A") + answer_idx)

        close.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "options": options,
            "answer": answer_letter,
        })
        open_.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "answer": f"The {obj} is moving {direction.lower()}",
        })
    return close, open_


def make_direction_obj_in_qa(samples):
    """조건4: 질문+답변 모두 object 이름 포함"""
    close, open_ = [], []

    for s in samples:
        obj = s["object"]
        direction = DIR_TO_LABEL[s["category"]]
        question = f"In which direction is the {obj} moving in this video?"

        options = [f"The {obj} is moving {d.lower()}" for d in DIRECTION_OPTIONS]
        answer_idx = DIRECTION_CLASSES.index(s["category"])
        answer_letter = chr(ord("A") + answer_idx)

        close.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "options": options,
            "answer": answer_letter,
        })
        open_.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "answer": f"The {obj} is moving {direction.lower()}",
        })
    return close, open_


def make_object_recognition(samples, all_objects):
    """조건5: object 종류 맞추기"""
    question = "What is the object moving in this video?"
    close, open_ = [], []

    for s in samples:
        obj = s["object"]
        obj_cap = obj.capitalize()

        # close-ended: 정답 + 랜덤 3개 오답 (중복 없이)
        distractors = [o for o in all_objects if o != obj]
        chosen = random.sample(distractors, min(3, len(distractors)))
        options_raw = [obj] + chosen
        random.shuffle(options_raw)
        options = [o.capitalize() for o in options_raw]
        answer_letter = chr(ord("A") + options_raw.index(obj))

        close.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "options": options,
            "answer": answer_letter,
        })
        open_.append({
            "video": s["video"], "category": s["category"],
            "question": question,
            "answer": obj_cap,
        })
    return close, open_


# ============================================================
# 생성 & 저장
# ============================================================
CONDITIONS = {
    "direction_only":     lambda s: make_direction_only(s),
    "direction_obj_in_q": lambda s: make_direction_obj_in_q(s),
    "direction_obj_in_a": lambda s: make_direction_obj_in_a(s),
    "direction_obj_in_qa": lambda s: make_direction_obj_in_qa(s),
    "object_recognition": lambda s: make_object_recognition(s, all_objects),
}

for cond_name, gen_fn in CONDITIONS.items():
    # 셔플된 복사본 사용
    shuffled = all_samples.copy()
    random.shuffle(shuffled)

    close_data, open_data = gen_fn(shuffled)

    # ID 부여
    for i, d in enumerate(close_data):
        d["id"] = i
    for i, d in enumerate(open_data):
        d["id"] = i

    # 저장
    close_path = os.path.join(OUTPUT_DIR, f"{cond_name}_close_ended.json")
    open_path = os.path.join(OUTPUT_DIR, f"{cond_name}_open_ended.json")

    with open(close_path, "w") as f:
        json.dump(close_data, f, indent=2, ensure_ascii=False)
    with open(open_path, "w") as f:
        json.dump(open_data, f, indent=2, ensure_ascii=False)

    print(f"\n[{cond_name}]")
    print(f"  close: {len(close_data)} → {close_path}")
    print(f"  open:  {len(open_data)} → {open_path}")
    # 샘플 출력
    print(f"  sample close: Q={close_data[0]['question']}")
    print(f"                options={close_data[0].get('options', 'N/A')}")
    print(f"                answer={close_data[0]['answer']}")
    print(f"  sample open:  Q={open_data[0]['question']}")
    print(f"                answer={open_data[0]['answer']}")

print(f"\n=== All done! {len(CONDITIONS) * 2} JSON files saved to {OUTPUT_DIR} ===")