main/main.py

import json
import os

def parse_face_attributes(json_file):
    with open(json_file, 'r', encoding='utf-8') as file:
        data = json.load(file)
    
    data = data[0]

    # 取出 faceAttributes 部分
    face_attr = data.get('faceAttributes', {})
    
    result = {}
    
    # 1. 笑容：若 smile 大於 0.1 則視為 "smiling"，否則 "no smile"
    smile_value = face_attr.get("smile", 0)
    result['smile'] = "smiling" if smile_value > 0.1 else "no smile"
    
    # 2. 頭部姿勢 (headPose)
    head_pose = face_attr.get("headPose", {})
    pitch = head_pose.get("pitch", 0)
    roll = head_pose.get("roll", 0)
    yaw = head_pose.get("yaw", 0)
    
    # pitch：大於 5 為 "upward"，小於 -5 為 "downward"，否則 "neutral"
    if pitch > 5:
        pitch_cat = "upward"
    elif pitch < -5:
        pitch_cat = "downward"
    else:
        pitch_cat = "neutral"
    
    # roll：絕對值大於 5 為 "tilted"，否則 "neutral"
    roll_cat = "tilted" if abs(roll) > 5 else "neutral"
    
    # yaw：大於 15 為 "turned right"，小於 -15 為 "turned left"，否則 "frontal"
    if yaw > 15:
        yaw_cat = "turned right"
    elif yaw < -15:
        yaw_cat = "turned left"
    else:
        yaw_cat = "frontal"
    
    result['headPose'] = {"pitch": pitch_cat, "roll": roll_cat, "yaw": yaw_cat}
    
    # 3. 性別 (gender)
    result["gender"] = face_attr.get("gender", "unknown")
    
    # 4. 年齡 (age)：依年齡數值分類
    age = face_attr.get("age", 0)
    if age < 2:
        age_cat = "baby"
    elif age < 10:
        age_cat = "child"
    elif age < 20:
        age_cat = "teenager"
    elif age < 60:
        age_cat = "adult"
    else:
        age_cat = "senior"
    result["age"] = age_cat
    
    # 5. 面部毛髮 (facialHair)：若各項均不超過 0.1 則為 "none"
    facial_hair = face_attr.get("facialHair", {})
    hair_types = []
    for key, value in facial_hair.items():
        if value > 0.1:
            hair_types.append(key)
    result["facialHair"] = "none" if not hair_types else ", ".join(hair_types)
    
    # 6. 眼鏡狀態 (glasses)
    result["glasses"] = face_attr.get("glasses", "NoGlasses")
    
    # 7. 情緒 (emotion)：取分數最高的情緒
    emotion = face_attr.get("emotion", {})
    if emotion:
        emotion_category = max(emotion, key=emotion.get)
    else:
        emotion_category = "unknown"
    result["emotion"] = emotion_category
    
    # 8. 模糊度 (blur)：以 blurLevel 為類別
    blur = face_attr.get("blur", {})
    result["blur"] = blur.get("blurLevel", "unknown")
    
    # 9. 曝光 (exposure)：以 exposureLevel 為類別
    exposure = face_attr.get("exposure", {})
    result["exposure"] = exposure.get("exposureLevel", "unknown")
    
    # 10. 噪音 (noise)：以 noiseLevel 為類別
    noise = face_attr.get("noise", {})
    result["noise"] = noise.get("noiseLevel", "unknown")
    
    # 11. 妝容 (makeup)：根據 eyeMakeup 與 lipMakeup 判斷
    makeup = face_attr.get("makeup", {})
    makeup_categories = []
    if makeup.get("eyeMakeup", False):
        makeup_categories.append("eye makeup")
    if makeup.get("lipMakeup", False):
        makeup_categories.append("lip makeup")
    result["makeup"] = "no makeup" if not makeup_categories else ", ".join(makeup_categories)
    
    # 12. 配件 (accessories)：若無配件則回傳 "none"
    accessories = face_attr.get("accessories", [])
    result["accessories"] = "none" if not accessories else ", ".join([acc.get("type", "unknown") for acc in accessories])
    
    # 13. 遮擋 (occlusion)：若皆為 False 則為 "none"，否則列出被遮擋的部位
    occlusion = face_attr.get("occlusion", {})
    occlusion_list = [k for k, v in occlusion.items() if v]
    result["occlusion"] = "none" if not occlusion_list else ", ".join(occlusion_list)
    
    # 14. 頭髮 (hair)：若 bald 大於 0.5 則為 "bald"，否則取 hairColor 中信心最高的顏色
    hair = face_attr.get("hair", {})
    if hair:
        if hair.get("bald", 0) > 0.5:
            hair_cat = "bald"
        else:
            hair_colors = hair.get("hairColor", [])
            if hair_colors:
                dominant_color = max(hair_colors, key=lambda x: x.get("confidence", 0))["color"]
            else:
                dominant_color = "unknown"
            hair_cat = dominant_color
    else:
        hair_cat = "unknown"
    result["hair"] = hair_cat
    
    return result

def record_all_categories(directory):
    """
    讀取指定目錄下所有 JSON 檔案，並統計每個屬性出現的所有類別
    """
    categories = {}  # 用來儲存各屬性的所有類別 (以 set 方式儲存避免重複)
    
    # 遍歷資料夾中所有 JSON 檔案
    error_cnt = 0
    for filename in os.listdir(directory):
        if not filename.endswith(".json"):
            continue
        file_path = os.path.join(directory, filename)
        try:
            parsed_result = parse_face_attributes(file_path)
        except Exception as e:
            error_cnt += 1
            # print(f"處理檔案 {filename} 時發生錯誤: {e}")
            continue
        
        # 將每個屬性對應的類別加入集合中
        for key, value in parsed_result.items():
            # 若屬性值為字典（例如 headPose），則進一步處理各子項
            if isinstance(value, dict):
                for sub_key, sub_val in value.items():
                    if sub_key not in categories:
                        categories[sub_key] = set()
                    categories[sub_key].add(sub_val)
            else:
                if key not in categories:
                    categories[key] = set()
                categories[key].add(value)
    print(f"總共處理 {len(os.listdir(directory))} 個檔案，其中 {error_cnt} 個檔案發生錯誤。")
    return categories

if __name__ == "__main__":
    # 設定 JSON 檔案所在目錄（請根據實際路徑修改）
    directory = "/root/siglip-recursion-ffhq-thumbnails/main/temp_data/ffhq-features-dataset/json"
    
    # 紀錄所有類別
    all_categories = record_all_categories(directory)
    
    # 印出各屬性出現的所有類別
    for attribute, values in all_categories.items():
        print(f"{attribute}: {', '.join(values)}")