add P16

app.py

@@ -1,5 +1,5 @@
 # ==============================================================================
-# evaluation_interface のコードブロック（修正済み）
+# evaluation_interface のコードブロック（セッションステート対応済み）
 # ==============================================================================
 import os
 import sys
@@ -12,31 +12,13 @@ from collections import defaultdict, Counter
 
 import gradio as gr
 from loguru import logger
-from PIL import Image  # ★ 修正点1: PILライブラリをインポート
+from PIL import Image
 import re
 
+# --- ★ 修正: GLOBAL_STATE を削除 ---
+# グローバルな状態管理を廃止し、Gradioのセッションステート (gr.State) に移行します。
 
-# --- Global State ---
-GLOBAL_STATE = {
-    "participant_id": None,
-    "data_loaded": False,
-    "all_eval_data": [],
-    "shuffled_indices": [],
-    "current_prompt_index": 0,
-    "current_criterion_index": 0,
-    "image_mapping": {},
-    "image_dir": "",
-    "evaluation_results": {},
-    "image_orders": {},
-    "start_time": None,
-    "end_time": None,
-    "current_ranks": {},
-    "current_absolute_score": None,
-    "current_absolute_score_worst": None,
-    "hide_bbox_dict": {},  # ★ 修正点2: マスキング情報を格納するキーを追加
-}
-
-# --- Configuration ---
+# --- Configuration (変更なし) ---
 BASE_RESULTS_DIR = "./results"
 LOG_DIR = "./logs"
 COMBINED_DATA_DIR = "./combined_data"
@@ -44,18 +26,6 @@ IMAGE_SUBDIR = os.path.join("lapwing", "images")
 MAPPING_FILENAME = "combination_to_filename.json"
 CONDITIONS = ["Ours", "w_o_Proto_Loss", "w_o_HitL", "w_o_Tuning", "LLM-based"]
 CRITERIA = ["Alignment", "Naturalness", "Attractiveness"]
-
-# CRITERIA_GUIDANCE_JP = [
-#     "テキストと表情がどれだけ一致しているか",
-#     "テキストの感情に沿ったセリフを言っていると想像したとき、表情がどれだけ自然か",
-#     "テキストの感情に沿ったセリフを言っていると想像したとき、表情がどれだけ魅力的か"
-# ]
-# CRITERIA_GUIDANCE_EN = [
-#     "how well the expression aligns with the text",
-#     "imagining the character is speaking a line that matches the emotion of the text, how natural the facial expression is",
-#     "imagining the character is speaking a line that matches the emotion of the text, how attractive the facial expression is"
-# ]
-
 CRITERIA_GUIDANCE_JP = [
     "テキストと上半分の表情がどれだけ一致していますか？",
     "提示されたテキストと上半分の表情を考慮した上で、このキャラクターはどれだけ自然に見えますか？",
@@ -69,24 +39,23 @@ CRITERIA_GUIDANCE_EN = [
 IMAGE_LABELS = ['A', 'B', 'C', 'D', 'E']
 
 
-# ★ 修正点3: マスキング用のヘルパー関数を classification_interface からコピー
-# --- Helper Functions ---
-def load_bbox_json(bbox_json_path):
-    """バウンディングボックス情報をJSONファイルから読み込む"""
+# --- Helper Functions (★ 修正: stateを引数に追加) ---
+def load_bbox_json(bbox_json_path, state):
+    """バウンディングボックス情報をJSONファイルから読み込み、stateに格納する"""
     try:
         with open(bbox_json_path, 'r', encoding='utf-8') as f:
             bbox_data = json.load(f)
-        # evaluation_interface では hide (隠す領域) のみ必要
-        GLOBAL_STATE["hide_bbox_dict"] = bbox_data.get("Hide", {})
+        state["hide_bbox_dict"] = bbox_data.get("Hide", {})
         logger.info(f"Successfully loaded bounding box data from {bbox_json_path}")
     except Exception as e:
         logger.error(f"Failed to load bounding box JSON: {e}")
-        GLOBAL_STATE["hide_bbox_dict"] = {}
+        state["hide_bbox_dict"] = {}
+    return state
 
 
-def create_masked_image(image: Image.Image):
+def create_masked_image(image: Image.Image, state: dict):
     """画像に黒塗りのマスクを適用する"""
-    hide_bbox_dict = GLOBAL_STATE.get("hide_bbox_dict", {})
+    hide_bbox_dict = state.get("hide_bbox_dict", {})
     if not hide_bbox_dict:
         return image
     masked_img = image.copy()
@@ -97,8 +66,8 @@ def create_masked_image(image: Image.Image):
     return masked_img
 
 
-def get_image_path_from_prediction(prediction: dict) -> str:
-    if not GLOBAL_STATE["image_mapping"]:
+def get_image_path_from_prediction(prediction: dict, state: dict) -> str:
+    if not state["image_mapping"]:
         logger.error("Image mapping is not loaded.")
         return ""
     indices = prediction.get("blendshape_index", {})
@@ -107,36 +76,35 @@ def get_image_path_from_prediction(prediction: dict) -> str:
         return ""
     sorted_indices = sorted(indices.items(), key=lambda item: int(item[0]))
     key = ",".join(str(idx) for _, idx in sorted_indices)
-    filename = GLOBAL_STATE["image_mapping"].get(key)
+    filename = state["image_mapping"].get(key)
     if not filename:
         logger.warning(f"No image found for blendshape key: {key}")
         return ""
-    return os.path.join(GLOBAL_STATE["image_dir"], filename)
+    return os.path.join(state["image_dir"], filename)
 
 
-def load_evaluation_data(participant_id: str):
-    # ★ 修正点4: バウンディングボックス情報を読み込む処理を追加
-    # classification_interfaceのパス構造を参考に、bboxファイルのパスを構築
+def load_evaluation_data(participant_id: str, state: dict):
+    """ ★ 修正: stateを引数で受け取り、更新したstateを返す """
     bbox_json_path = os.path.join(COMBINED_DATA_DIR, "lapwing", "texts", "bounding_boxes.json")
     if os.path.exists(bbox_json_path):
-        load_bbox_json(bbox_json_path)
+        state = load_bbox_json(bbox_json_path, state)
     else:
         logger.warning(f"Bounding box file not found at {bbox_json_path}. Images will not be masked.")
-        GLOBAL_STATE["hide_bbox_dict"] = {}
+        state["hide_bbox_dict"] = {}
 
     mapping_path = os.path.join(COMBINED_DATA_DIR, MAPPING_FILENAME)
     if not os.path.exists(mapping_path):
-        return f"<p class='feedback red'>Error: Mapping file not found at {mapping_path}</p>", gr.update(
+        return state, f"<p class='feedback red'>Error: Mapping file not found at {mapping_path}</p>", gr.update(
             interactive=True), gr.update(interactive=False)
 
     with open(mapping_path, 'r', encoding='utf-8') as f:
-        GLOBAL_STATE["image_mapping"] = json.load(f)["mapping"]
-    GLOBAL_STATE["image_dir"] = os.path.join(COMBINED_DATA_DIR, IMAGE_SUBDIR)
-    logger.info(f"Successfully loaded image mapping. Image directory: {GLOBAL_STATE['image_dir']}")
+        state["image_mapping"] = json.load(f)["mapping"]
+    state["image_dir"] = os.path.join(COMBINED_DATA_DIR, IMAGE_SUBDIR)
+    logger.info(f"Successfully loaded image mapping. Image directory: {state['image_dir']}")
 
     participant_dir = os.path.join(BASE_RESULTS_DIR, participant_id)
     if not os.path.isdir(participant_dir):
-        return f"<p class='feedback red'>Error: Participant directory not found: {participant_dir}</p>", gr.update(
+        return state, f"<p class='feedback red'>Error: Participant directory not found: {participant_dir}</p>", gr.update(
             interactive=True), gr.update(interactive=False)
 
     merged_data = defaultdict(lambda: {"predictions": {}, "category": None})
@@ -158,38 +126,38 @@ def load_evaluation_data(participant_id: str):
                     merged_data[prompt]["category"] = data.get("prompt_category")
 
     if found_files != len(CONDITIONS):
-        return f"<p class='feedback red'>Error: Found prediction files for only {found_files}/{len(CONDITIONS)} conditions.</p>", gr.update(
+        return state, f"<p class='feedback red'>Error: Found prediction files for only {found_files}/{len(CONDITIONS)} conditions.</p>", gr.update(
             interactive=True), gr.update(interactive=False)
 
-    GLOBAL_STATE["all_eval_data"] = [
+    state["all_eval_data"] = [
         {"prompt": p, "predictions": d["predictions"], "category": d["category"]}
         for p, d in merged_data.items() if len(d["predictions"]) == len(CONDITIONS)
     ]
 
-    if not GLOBAL_STATE["all_eval_data"]:
-        return "<p class='feedback red'>Error: No valid evaluation data could be loaded.</p>", gr.update(
+    if not state["all_eval_data"]:
+        return state, "<p class='feedback red'>Error: No valid evaluation data could be loaded.</p>", gr.update(
             interactive=True), gr.update(interactive=False)
 
-    GLOBAL_STATE["shuffled_indices"] = list(range(len(GLOBAL_STATE["all_eval_data"])))
-    random.shuffle(GLOBAL_STATE["shuffled_indices"])
-    GLOBAL_STATE["current_prompt_index"] = 0
-    GLOBAL_STATE["current_criterion_index"] = 0
-    GLOBAL_STATE["data_loaded"] = True
-    GLOBAL_STATE["start_time"] = datetime.now()
-    for i in range(len(GLOBAL_STATE["all_eval_data"])):
-        prompt_text = GLOBAL_STATE["all_eval_data"][i]["prompt"]
-        GLOBAL_STATE["evaluation_results"][prompt_text] = {}
-
-    logger.info(f"Loaded and merged data for {len(GLOBAL_STATE['all_eval_data'])} prompts.")
+    state["shuffled_indices"] = list(range(len(state["all_eval_data"])))
+    random.shuffle(state["shuffled_indices"])
+    state["current_prompt_index"] = 0
+    state["current_criterion_index"] = 0
+    state["data_loaded"] = True
+    state["start_time"] = datetime.now()
+    for i in range(len(state["all_eval_data"])):
+        prompt_text = state["all_eval_data"][i]["prompt"]
+        state["evaluation_results"][prompt_text] = {}
+
+    logger.info(f"Loaded and merged data for {len(state['all_eval_data'])} prompts.")
     done_msg = "<p class='feedback green'>Data loaded successfully. Please proceed to the 'Evaluation' tab. / データの読み込みに成功しました。「評価」タブに進んでください。</p>"
-    return done_msg, gr.update(interactive=False, visible=False), gr.update(interactive=True)
+    return state, done_msg, gr.update(interactive=False, visible=False), gr.update(interactive=True)
 
 
-# --- Core Logic (unchanged) ---
-def _create_button_updates():
+# --- Core Logic (★ 修正: stateを引数に追加) ---
+def _create_button_updates(state: dict):
     updates = []
     for img_label in IMAGE_LABELS:
-        selected_rank = GLOBAL_STATE["current_ranks"].get(img_label)
+        selected_rank = state["current_ranks"].get(img_label)
         for rank_val in range(1, 6):
             if rank_val == selected_rank:
                 updates.append(gr.update(variant='primary'))
@@ -198,75 +166,77 @@ def _create_button_updates():
     return updates
 
 
-def handle_rank_button_click(image_label, rank):
-    if GLOBAL_STATE["current_ranks"].get(image_label) == rank:
-        GLOBAL_STATE["current_ranks"][image_label] = None
+def handle_rank_button_click(image_label, rank, state: dict):
+    if state["current_ranks"].get(image_label) == rank:
+        state["current_ranks"][image_label] = None
     else:
-        GLOBAL_STATE["current_ranks"][image_label] = rank
-    return _create_button_updates()
+        state["current_ranks"][image_label] = rank
+    return state, *_create_button_updates(state)
 
 
-def handle_absolute_score_click(score):
-    if GLOBAL_STATE["current_absolute_score"] == score:
-        GLOBAL_STATE["current_absolute_score"] = None
+def handle_absolute_score_click(score, state: dict):
+    if state["current_absolute_score"] == score:
+        state["current_absolute_score"] = None
     else:
-        GLOBAL_STATE["current_absolute_score"] = score
+        state["current_absolute_score"] = score
     updates = []
     for i in range(1, 8):
-        if i == GLOBAL_STATE["current_absolute_score"]:
+        if i == state["current_absolute_score"]:
             updates.append(gr.update(variant='primary'))
         else:
             updates.append(gr.update(variant='secondary'))
-    return updates
+    return state, *updates
 
 
-def handle_absolute_score_worst_click(score):
-    if GLOBAL_STATE["current_absolute_score_worst"] == score:
-        GLOBAL_STATE["current_absolute_score_worst"] = None
+def handle_absolute_score_worst_click(score, state: dict):
+    if state["current_absolute_score_worst"] == score:
+        state["current_absolute_score_worst"] = None
     else:
-        GLOBAL_STATE["current_absolute_score_worst"] = score
+        state["current_absolute_score_worst"] = score
     updates = []
     for i in range(1, 8):
-        if i == GLOBAL_STATE["current_absolute_score_worst"]:
+        if i == state["current_absolute_score_worst"]:
             updates.append(gr.update(variant='primary'))
         else:
             updates.append(gr.update(variant='secondary'))
-    return updates
+    return state, *updates
 
 
-# --- UI Logic ---
-def display_current_prompt_and_criterion():
-    if not GLOBAL_STATE["data_loaded"] or GLOBAL_STATE["current_prompt_index"] >= len(GLOBAL_STATE["all_eval_data"]):
+# --- UI Logic (★ 修正: stateを引数に追加) ---
+def display_current_prompt_and_criterion(state: dict):
+    if not state["data_loaded"] or state["current_prompt_index"] >= len(state["all_eval_data"]):
         done_msg = "<p class='feedback green' style='text-align: center; font-size: 1.2em;'>All prompts have been evaluated! Please proceed to the 'Export' tab. <br>すべてのプロンプトの評価が完了しました！「エクスポート」タブに進んでください。</p>"
         empty_button_updates = [gr.update(variant='secondary')] * 25
         empty_abs_updates = [gr.update(variant='secondary')] * 7
         return [
-            gr.update(value="Finished! / 完了!"),  # progress_text
-            gr.update(value=""),  # combined_instructions_display
-            gr.update(value=""),  # prompt_display
-            gr.update(value=done_msg, visible=True),  # error_display
+            gr.update(value="Finished! / 完了!"),
+            gr.update(value=""),
+            gr.update(value=""),
+            gr.update(value=done_msg, visible=True),
             *[gr.update(value=None)] * 5,
             *empty_button_updates,
-            gr.update(visible=False),  # abs_group_best
+            gr.update(visible=False),
             *empty_abs_updates,
-            gr.update(visible=False),  # abs_group_worst
+            gr.update(visible=False),
             *empty_abs_updates,
             gr.update(interactive=False),
             gr.update(interactive=False)
         ]
 
-    prompt_idx = GLOBAL_STATE["shuffled_indices"][GLOBAL_STATE["current_prompt_index"]]
-    criterion_idx = GLOBAL_STATE["current_criterion_index"]
+    prompt_idx = state["shuffled_indices"][state["current_prompt_index"]]
+    criterion_idx = state["current_criterion_index"]
 
-    current_data = GLOBAL_STATE["all_eval_data"][prompt_idx]
+    current_data = state["all_eval_data"][prompt_idx]
     prompt_text = current_data["prompt"]
     criterion_name = CRITERIA[criterion_idx]
 
-    progress_text = f"Prompt {GLOBAL_STATE['current_prompt_index'] + 1} / {len(GLOBAL_STATE['all_eval_data'])}  -  **{criterion_name}**"
+    progress_text = f"Prompt {state['current_prompt_index'] + 1} / {len(state['all_eval_data'])}  -  **{criterion_name}**"
     prompt_display_text = f"<p style='font-size: 3em; font-weight: bold;'>テキスト(TEXT): {prompt_text}</p>"
+    # (Instructions text is unchanged)
     guidance_part = (
         f"<p style='color: red; font-weight: bold; font-size: 1.1em;'>"
         f"5つの画像を、「{CRITERIA_GUIDANCE_JP[criterion_idx]}」を基準にランキングしてください。<br>"
+        f"「ランキングの方法」をよく読んでつけてください。<br>"
         f"Please rank the 5 images based on {CRITERIA_GUIDANCE_EN[criterion_idx]}"
         f"</p>"
     )
@@ -291,23 +261,22 @@ def display_current_prompt_and_criterion():
     combined_instructions = f"{guidance_part}<hr>{rules_part}<hr>{ai_note_part}"
 
     if criterion_idx == 0:
-        GLOBAL_STATE["image_orders"] = {}
+        state["image_orders"] = {}
 
-    if criterion_name not in GLOBAL_STATE["image_orders"]:
+    if criterion_name not in state["image_orders"]:
         conditions_shuffled = random.sample(CONDITIONS, len(CONDITIONS))
-        GLOBAL_STATE["image_orders"][criterion_name] = conditions_shuffled
+        state["image_orders"][criterion_name] = conditions_shuffled
 
-    current_image_order = GLOBAL_STATE["image_orders"][criterion_name]
+    current_image_order = state["image_orders"][criterion_name]
     image_updates = []
     for cond_name in current_image_order:
         prediction = current_data["predictions"][cond_name]
-        img_path = get_image_path_from_prediction(prediction)
+        img_path = get_image_path_from_prediction(prediction, state)
 
-        # ★ 修正点5: 画像を読み込み、マスキングを適用する
         if img_path and os.path.exists(img_path):
             try:
                 pil_img = Image.open(img_path).convert('RGB')
-                masked_img = create_masked_image(pil_img)
+                masked_img = create_masked_image(pil_img, state)
                 image_updates.append(gr.update(value=masked_img))
             except Exception as e:
                 logger.error(f"Failed to open or mask image {img_path}: {e}")
@@ -315,42 +284,42 @@ def display_current_prompt_and_criterion():
         else:
             image_updates.append(gr.update(value=None))
 
-    saved_ranks_dict = GLOBAL_STATE["evaluation_results"].get(prompt_text, {}).get("ranks", {}).get(criterion_name)
+    saved_ranks_dict = state["evaluation_results"].get(prompt_text, {}).get("ranks", {}).get(criterion_name)
     if saved_ranks_dict:
         label_to_condition = {label: cond for label, cond in zip(IMAGE_LABELS, current_image_order)}
         condition_to_label = {v: k for k, v in label_to_condition.items()}
-        GLOBAL_STATE["current_ranks"] = {
+        state["current_ranks"] = {
             condition_to_label[cond]: rank for cond, rank in saved_ranks_dict.items() if cond in condition_to_label
         }
     else:
-        GLOBAL_STATE["current_ranks"] = {label: None for label in IMAGE_LABELS}
+        state["current_ranks"] = {label: None for label in IMAGE_LABELS}
 
-    button_updates = _create_button_updates()
+    button_updates = _create_button_updates(state)
 
     is_alignment_criterion = (criterion_name == "Alignment")
     abs_group_update = gr.update(visible=is_alignment_criterion)
-    saved_abs_score = GLOBAL_STATE["evaluation_results"].get(prompt_text, {}).get("absolute_score")
-    GLOBAL_STATE["current_absolute_score"] = saved_abs_score if is_alignment_criterion else None
+    saved_abs_score = state["evaluation_results"].get(prompt_text, {}).get("absolute_score")
+    state["current_absolute_score"] = saved_abs_score if is_alignment_criterion else None
 
     abs_button_updates = []
     for i in range(1, 8):
-        variant = 'primary' if i == GLOBAL_STATE["current_absolute_score"] else 'secondary'
+        variant = 'primary' if i == state["current_absolute_score"] else 'secondary'
         abs_button_updates.append(gr.update(variant=variant))
 
     abs_group_worst_update = gr.update(visible=is_alignment_criterion)
-    saved_abs_score_worst = GLOBAL_STATE["evaluation_results"].get(prompt_text, {}).get("absolute_score_worst")
-    GLOBAL_STATE["current_absolute_score_worst"] = saved_abs_score_worst if is_alignment_criterion else None
+    saved_abs_score_worst = state["evaluation_results"].get(prompt_text, {}).get("absolute_score_worst")
+    state["current_absolute_score_worst"] = saved_abs_score_worst if is_alignment_criterion else None
 
     abs_button_worst_updates = []
     for i in range(1, 8):
-        variant = 'primary' if i == GLOBAL_STATE["current_absolute_score_worst"] else 'secondary'
+        variant = 'primary' if i == state["current_absolute_score_worst"] else 'secondary'
         abs_button_worst_updates.append(gr.update(variant=variant))
 
     return [
         gr.update(value=progress_text),
         gr.update(value=combined_instructions),
         gr.update(value=prompt_display_text),
-        gr.update(value="", visible=False),  # Error display
+        gr.update(value="", visible=False),
         *image_updates,
         *button_updates,
         abs_group_update,
@@ -358,31 +327,30 @@ def display_current_prompt_and_criterion():
         abs_group_worst_update,
         *abs_button_worst_updates,
         gr.update(
-            interactive=(GLOBAL_STATE["current_prompt_index"] > 0 or GLOBAL_STATE["current_criterion_index"] > 0)),
+            interactive=(state["current_prompt_index"] > 0 or state["current_criterion_index"] > 0)),
         gr.update(interactive=True)
     ]
 
 
-# --- (以降の関数は変更なし) ---
-def validate_and_navigate():
-    ranks = GLOBAL_STATE["current_ranks"]
+def validate_and_navigate(state: dict):
+    ranks = state["current_ranks"]
     error_msg = None
-    criterion_name = CRITERIA[GLOBAL_STATE["current_criterion_index"]]
+    criterion_name = CRITERIA[state["current_criterion_index"]]
     is_alignment_criterion = (criterion_name == "Alignment")
 
     if any(r is None for r in ranks.values()):
         error_msg = "Please rank all 5 images. / 5つすべての画像を評価してください。"
     elif 1 not in ranks.values():
         error_msg = "You must assign a rank of '1' to at least one image. / 最低1つは「1位」を付けてください。"
-    elif is_alignment_criterion and GLOBAL_STATE["current_absolute_score"] is None:
+    elif is_alignment_criterion and state["current_absolute_score"] is None:
         error_msg = "Please provide an absolute score for the BEST matching image (1-7). / 最も一致している画像について、絶対評価（1～7）を選択してください。"
-    elif is_alignment_criterion and GLOBAL_STATE["current_absolute_score_worst"] is None:
+    elif is_alignment_criterion and state["current_absolute_score_worst"] is None:
         error_msg = "Please provide an absolute score for the WORST matching image (1-7). / 最も一致していない画像について、絶対評価（1～7）を選択してください。"
     elif (
             is_alignment_criterion
-            and GLOBAL_STATE["current_absolute_score"] is not None
-            and GLOBAL_STATE["current_absolute_score_worst"] is not None
-            and GLOBAL_STATE["current_absolute_score_worst"] > GLOBAL_STATE["current_absolute_score"]
+            and state["current_absolute_score"] is not None
+            and state["current_absolute_score_worst"] is not None
+            and state["current_absolute_score_worst"] > state["current_absolute_score"]
     ):
         error_msg = (
             "The score for the WORST matching image cannot be higher than the score for the BEST matching image.<br>"
@@ -390,11 +358,15 @@ def validate_and_navigate():
         )
 
     if error_msg:
-        no_change_updates = [gr.update()] * 53
-        no_change_updates[4] = gr.update(
+        # ★ 修正点: no_change_updates の要素数を 52 に変更
+        no_change_updates = [gr.update()] * 52
+        # error_display は all_eval_outputs の4番目(インデックス3)のコンポーネント
+        no_change_updates[3] = gr.update(
             value=f"<p class='feedback red' style='font-size: 1.2em; text-align: center;'>{error_msg}</p>",
             visible=True)
-        return no_change_updates
+        # 戻り値の総数が54個 (state, tab_exportの更新, all_eval_outputsの更新) になるように調整
+        return state, gr.update(), *no_change_updates
+
 
     sorted_ranks = sorted(list(ranks.values()))
     rank_counts = Counter(sorted_ranks)
@@ -410,59 +382,70 @@ def validate_and_navigate():
                 break
         i += count
     if error_msg:
-        no_change_updates = [gr.update()] * 53
-        no_change_updates[4] = gr.update(
+        # ★ 修正点: こちらも同様に no_change_updates の要素数を 52 に変更
+        no_change_updates = [gr.update()] * 52
+        # error_display は all_eval_outputs の4番目(インデックス3)のコンポーネント
+        no_change_updates[3] = gr.update(
             value=f"<p class='feedback red' style='font-size: 1.2em; text-align: center;'>{error_msg}</p>",
             visible=True)
-        return no_change_updates
+        # 戻り値の総数が54個になるように調整
+        return state, gr.update(), *no_change_updates
 
-    prompt_idx = GLOBAL_STATE["shuffled_indices"][GLOBAL_STATE["current_prompt_index"]]
-    current_data = GLOBAL_STATE["all_eval_data"][prompt_idx]
+    prompt_idx = state["shuffled_indices"][state["current_prompt_index"]]
+    current_data = state["all_eval_data"][prompt_idx]
     prompt_text = current_data["prompt"]
-    current_image_order = GLOBAL_STATE["image_orders"][criterion_name]
+    current_image_order = state["image_orders"][criterion_name]
 
     label_to_condition = {label: cond for label, cond in zip(IMAGE_LABELS, current_image_order)}
     ranks_by_condition = {label_to_condition[label]: rank for label, rank in ranks.items()}
 
-    if "ranks" not in GLOBAL_STATE["evaluation_results"][prompt_text]:
-        GLOBAL_STATE["evaluation_results"][prompt_text]["ranks"] = {}
-    if "orders" not in GLOBAL_STATE["evaluation_results"][prompt_text]:
-        GLOBAL_STATE["evaluation_results"][prompt_text]["orders"] = {}
+    if "ranks" not in state["evaluation_results"][prompt_text]:
+        state["evaluation_results"][prompt_text]["ranks"] = {}
+    if "orders" not in state["evaluation_results"][prompt_text]:
+        state["evaluation_results"][prompt_text]["orders"] = {}
+
+    state["evaluation_results"][prompt_text]["ranks"][criterion_name] = ranks_by_condition
+    state["evaluation_results"][prompt_text]["orders"][criterion_name] = current_image_order
+
+    logger.info(
+        f"Saved rank for P:{state['participant_id']}, Prompt:'{prompt_text}', Criterion:{criterion_name}, Ranks:{ranks_by_condition}, Orders:{current_image_order}, ")
 
-    GLOBAL_STATE["evaluation_results"][prompt_text]["ranks"][criterion_name] = ranks_by_condition
-    GLOBAL_STATE["evaluation_results"][prompt_text]["orders"][criterion_name] = current_image_order
 
     if is_alignment_criterion:
-        GLOBAL_STATE["evaluation_results"][prompt_text]["absolute_score"] = GLOBAL_STATE["current_absolute_score"]
-        GLOBAL_STATE["evaluation_results"][prompt_text]["absolute_score_worst"] = GLOBAL_STATE[
-            "current_absolute_score_worst"]
+        state["evaluation_results"][prompt_text]["absolute_score"] = state["current_absolute_score"]
+        state["evaluation_results"][prompt_text]["absolute_score_worst"] = state["current_absolute_score_worst"]
 
-    logger.info(
-        f"Saved rank for P:{GLOBAL_STATE['participant_id']}, Prompt:'{prompt_text}', Criterion:{criterion_name}, Ranks:{ranks_by_condition}")
+        logger.info(
+            f"Saved absolute scores for P:{state['participant_id']}, Prompt:'{prompt_text}', "
+            f"Best Score:{state['current_absolute_score']}, Worst Score:{state['current_absolute_score_worst']}")
 
-    GLOBAL_STATE["current_criterion_index"] += 1
-    if GLOBAL_STATE["current_criterion_index"] >= len(CRITERIA):
-        GLOBAL_STATE["current_criterion_index"] = 0
-        GLOBAL_STATE["current_prompt_index"] += 1
 
-    if GLOBAL_STATE["current_prompt_index"] >= len(GLOBAL_STATE["all_eval_data"]):
-        GLOBAL_STATE["end_time"] = datetime.now()
-        eval_panel_updates = display_current_prompt_and_criterion()
-        return [gr.update(interactive=True)] + eval_panel_updates
-    else:
-        return [gr.update()] + display_current_prompt_and_criterion()
+    state["current_criterion_index"] += 1
+    if state["current_criterion_index"] >= len(CRITERIA):
+        state["current_criterion_index"] = 0
+        state["current_prompt_index"] += 1
+
+    if state["current_prompt_index"] >= len(state["all_eval_data"]):
+        state["end_time"] = datetime.now()
+
+    eval_panel_updates = display_current_prompt_and_criterion(state)
+    export_tab_update = gr.update(interactive=(state.get("end_time") is not None))
+    return state, export_tab_update, *eval_panel_updates
 
 
-def navigate_previous():
-    GLOBAL_STATE["current_criterion_index"] -= 1
-    if GLOBAL_STATE["current_criterion_index"] < 0:
-        GLOBAL_STATE["current_criterion_index"] = len(CRITERIA) - 1
-        GLOBAL_STATE["current_prompt_index"] -= 1
-    GLOBAL_STATE["current_prompt_index"] = max(0, GLOBAL_STATE["current_prompt_index"])
-    return display_current_prompt_and_criterion()
+def navigate_previous(state: dict):
+    state["current_criterion_index"] -= 1
+    if state["current_criterion_index"] < 0:
+        state["current_criterion_index"] = len(CRITERIA) - 1
+        state["current_prompt_index"] -= 1
+    state["current_prompt_index"] = max(0, state["current_prompt_index"])
 
+    # ★ 修正: display_current_prompt_and_criterion は state を返さないので、ここで state を返す
+    return state, *display_current_prompt_and_criterion(state)
 
-def export_results(participant_id, alignment_reason, naturalness_reason, attractiveness_reason, optional_comment):
+
+def export_results(participant_id, alignment_reason, naturalness_reason, attractiveness_reason, optional_comment,
+                   state: dict):
     if not alignment_reason.strip() or not naturalness_reason.strip() or not attractiveness_reason.strip():
         error_msg = "<p class='feedback red'>Please fill in the reasoning for all three criteria (Alignment, Naturalness, Attractiveness). / 3つの評価基準（一致度, 自然さ, 魅力度）すべての判断理由を記入してください。</p>"
         return None, error_msg
@@ -475,15 +458,15 @@ def export_results(participant_id, alignment_reason, naturalness_reason, attract
     filename = f"evaluation_results_{participant_id}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
     filepath = os.path.join(output_dir, filename)
 
-    duration = (GLOBAL_STATE["end_time"] - GLOBAL_STATE["start_time"]).total_seconds() if GLOBAL_STATE.get(
-        "start_time") and GLOBAL_STATE.get("end_time") else None
+    duration = (state["end_time"] - state["start_time"]).total_seconds() if state.get(
+        "start_time") and state.get("end_time") else None
 
-    prompt_to_category = {item["prompt"]: item["category"] for item in GLOBAL_STATE["all_eval_data"]}
+    prompt_to_category = {item["prompt"]: item["category"] for item in state["all_eval_data"]}
 
     final_results_list = []
-    for prompt, data in GLOBAL_STATE["evaluation_results"].items():
+    for prompt, data in state["evaluation_results"].items():
         if not data: continue
-
+        # (以降、データ構造の作成部分は変更なし)
         ranks_data = data.get("ranks", {})
         orders_data = data.get("orders", {})
 
@@ -516,6 +499,8 @@ def export_results(participant_id, alignment_reason, naturalness_reason, attract
         "results": final_results_list
     }
 
+    logger.info(f"Exporting results for participant metadata: {export_data['metadata']}")
+
     try:
         with open(filepath, 'w', encoding='utf-8') as f:
             json.dump(export_data, f, ensure_ascii=False, indent=2)
@@ -537,6 +522,7 @@ def export_results(participant_id, alignment_reason, naturalness_reason, attract
 
 def create_gradio_interface():
     css = """
+    /* (CSSは変更なし) */
     .gradio-container { font-family: 'Arial', sans-serif; }
     .feedback { padding: 10px; border-radius: 5px; font-weight: bold; text-align: center; margin-top: 10px; }
     .feedback.green { background-color: #e6ffed; color: #2f6f4a; }
@@ -544,44 +530,41 @@ def create_gradio_interface():
     .image-label { font-size: 2.5em; font-weight: bold; margin-bottom: 10px; color: #333; }
     .prompt-display { text-align: center; margin-bottom: 15px; padding: 10px; background-color: #f0f8ff; border-radius: 8px; }
     .rank-btn-row { justify-content: center; gap: 5px !important; }
-    .rank-btn {
-        min-width: 65px !important;
-        max-width: 65px !important;
-        height: 45px !important;
-        font-size: 1.2em !important;
-        font-weight: bold !important;
-        border-radius: 8px !important;
-        border: 1px solid #ccc !important;
-    }
-    .rank-btn.secondary {
-        background: #f0f0f0 !important;
-        color: #333 !important;
-    }
-    .rank-btn.secondary:hover {
-        background: #e0e0e0 !important;
-        border-color: #bbb !important;
-    }
-    .absolute-eval-group {
-        border: 1px solid #ddd;
-        border-radius: 8px;
-        padding: 15px;
-        margin-top: 20px;
-    }
-    .instructions-container {
-        padding: 15px;
-        border: 1px solid #ccc;
-        border-radius: 8px;
-        margin-bottom: 20px;
-        background-color: #fafafa;
-    }
+    .rank-btn { min-width: 65px !important; max-width: 65px !important; height: 45px !important; font-size: 1.2em !important; font-weight: bold !important; border-radius: 8px !important; border: 1px solid #ccc !important; }
+    .rank-btn.secondary { background: #f0f0f0 !important; color: #333 !important; }
+    .rank-btn.secondary:hover { background: #e0e0e0 !important; border-color: #bbb !important; }
+    .absolute-eval-group { border: 1px solid #ddd; border-radius: 8px; padding: 15px; margin-top: 20px; }
+    .instructions-container { padding: 15px; border: 1px solid #ccc; border-radius: 8px; margin-bottom: 20px; background-color: #fafafa; }
     .instructions-container ul { padding-left: 20px; margin-top: 5px; margin-bottom: 5px; }
     .instructions-container hr { margin: 15px 0; }
     """
 
     with gr.Blocks(title="Expression Evaluation Experiment", css=css) as app:
+        # ★ 修正: セッションステート (gr.State) を初期化
+        initial_state = {
+            "participant_id": None,
+            "data_loaded": False,
+            "all_eval_data": [],
+            "shuffled_indices": [],
+            "current_prompt_index": 0,
+            "current_criterion_index": 0,
+            "image_mapping": {},
+            "image_dir": "",
+            "evaluation_results": {},
+            "image_orders": {},
+            "start_time": None,
+            "end_time": None,
+            "current_ranks": {},
+            "current_absolute_score": None,
+            "current_absolute_score_worst": None,
+            "hide_bbox_dict": {},
+        }
+        state = gr.State(value=initial_state)
+
         gr.Markdown("# Text-to-Expression Evaluation Experiment / テキストからの表情生成 評価実験")
 
         with gr.Tabs() as tabs:
+            # (UI定義は変更なし)
             with gr.TabItem("1. Setup / セットアップ") as tab_setup:
                 gr.Markdown("## (A) Participant Information / 参加者情報")
                 gr.Markdown("Please enter your participant ID and click 'Confirm'. / 参加者IDを入力して「確定」を押してください。")
@@ -599,6 +582,7 @@ def create_gradio_interface():
                             <li><b>この作業はPCで行ってください。/ Please perform this task on a PC.</b></li>
                             <li>途中で止めずに最後まで続けてください。ファイルをアップロードして完了となります。/ Please continue until the end. The experiment is complete when you upload the file.</li>
                             <li>ブラウザーをリロードしないでください (データが破損します)。/ Do not reload the browser (this will corrupt the data).</li>
+                            <li><b>指示と注意書きをよく読んでください。</b></li>
                         </ul></div>""")
                     gr.Markdown(
                         "Click the button below to load your evaluation data. / 下のボタンを押して、評価データを読み込んでください。")
@@ -618,7 +602,7 @@ def create_gradio_interface():
                         with gr.Column(scale=1):
                             with gr.Group():
                                 gr.Markdown(f"<div class='image-label' style='text-align: center;'>{label}</div>")
-                                img = gr.Image(type="pil", show_label=False, height=300)  # typeを"pil"に変更
+                                img = gr.Image(type="pil", show_label=False, height=300)
                                 image_components.append(img)
                                 with gr.Row(elem_classes="rank-btn-row"):
                                     rank_list = ["1位", "2位", "3位", "4位", "5位"]
@@ -691,18 +675,20 @@ def create_gradio_interface():
                 download_file = gr.File(label="Download JSON", visible=False)
                 export_status = gr.Markdown()
 
-        # --- Event Handlers ---
-        def check_and_confirm_id(pid):
+        # --- Event Handlers (★ 修正: stateを入出力に追加) ---
+        def check_and_confirm_id(pid, state):
             pid = pid.strip()
             if re.fullmatch(r"P\d{2}", pid):
-                GLOBAL_STATE["participant_id"] = pid
-                return gr.update(visible=False), gr.update(visible=True)
+                state["participant_id"] = pid
+                return state, gr.update(visible=False), gr.update(visible=True)
             else:
                 error_msg = "<p class='feedback red'>Invalid ID. Must be 'P' followed by two digits (e.g., P01). / 無効なIDです。「P」と数字2桁の形式（例: P01）で入力してください。</p>"
-                return gr.update(value=error_msg, visible=True), gr.update(visible=False)
+                return state, gr.update(value=error_msg, visible=True), gr.update(visible=False)
 
-        confirm_id_btn.click(check_and_confirm_id, [participant_id_input], [setup_warning, setup_main_group])
-        load_data_btn.click(load_evaluation_data, [participant_id_input], [setup_status, load_data_btn, tab_evaluation])
+        confirm_id_btn.click(check_and_confirm_id, [participant_id_input, state],
+                             [state, setup_warning, setup_main_group])
+        load_data_btn.click(load_evaluation_data, [participant_id_input, state],
+                            [state, setup_status, load_data_btn, tab_evaluation])
 
         all_eval_outputs = [
             progress_text, combined_instructions_display, prompt_display, error_display, *image_components,
@@ -716,45 +702,48 @@ def create_gradio_interface():
         for label in IMAGE_LABELS:
             for rank_val in range(1, 6):
                 btn = rank_buttons[btn_idx]
+                # functools.partial を使うことで、state以外の引数を固定できます
                 btn.click(
                     partial(handle_rank_button_click, label, rank_val),
-                    [],
-                    rank_buttons
+                    [state],
+                    [state, *rank_buttons]
                 )
                 btn_idx += 1
 
         for i, btn in enumerate(absolute_score_buttons):
             btn.click(
                 partial(handle_absolute_score_click, i + 1),
-                [],
-                absolute_score_buttons
+                [state],
+                [state, *absolute_score_buttons]
             )
 
         for i, btn in enumerate(absolute_score_worst_buttons):
             btn.click(
                 partial(handle_absolute_score_worst_click, i + 1),
-                [],
-                absolute_score_worst_buttons
+                [state],
+                [state, *absolute_score_worst_buttons]
             )
 
-        tab_evaluation.select(display_current_prompt_and_criterion, [], all_eval_outputs)
-        next_btn.click(validate_and_navigate, [], [tab_export, *all_eval_outputs])
-        prev_btn.click(navigate_previous, [], all_eval_outputs)
+        tab_evaluation.select(display_current_prompt_and_criterion, [state], all_eval_outputs)
+
+        # next_btn と prev_btn の出力に state を追加
+        next_btn.click(validate_and_navigate, [state], [state, tab_export, *all_eval_outputs])
+        prev_btn.click(navigate_previous, [state], [state, *all_eval_outputs])
 
         export_tab_interactive_components = [alignment_reason_box, naturalness_reason_box, attractiveness_reason_box,
                                              optional_comment_box, export_btn]
 
-        def on_select_export_tab():
-            if GLOBAL_STATE.get("end_time"):
+        def on_select_export_tab(state):
+            if state.get("end_time"):
                 return [gr.update(interactive=True)] * 5
             return [gr.update(interactive=False)] * 5
 
-        tab_export.select(on_select_export_tab, [], export_tab_interactive_components)
+        tab_export.select(on_select_export_tab, [state], export_tab_interactive_components)
 
         export_btn.click(
             export_results,
             [participant_id_input, alignment_reason_box, naturalness_reason_box, attractiveness_reason_box,
-             optional_comment_box],
+             optional_comment_box, state],
             [download_file, export_status]
         )
 

logs/evaluation_ui_log_2025-08-02_14-41-24_427858.log

@@ -0,0 +1,3 @@
+2025-08-02 14:41:39.852 | INFO     | __main__:load_bbox_json:49 - Successfully loaded bounding box data from ./combined_data\lapwing\texts\bounding_boxes.json
+2025-08-02 14:41:39.853 | INFO     | __main__:load_evaluation_data:103 - Successfully loaded image mapping. Image directory: ./combined_data\lapwing\images
+2025-08-02 14:41:39.855 | INFO     | __main__:load_evaluation_data:151 - Loaded and merged data for 28 prompts.

logs/evaluation_ui_log_2025-08-02_14-47-08_666920.log

@@ -0,0 +1,6 @@
+2025-08-02 14:47:18.374 | INFO     | __main__:load_bbox_json:49 - Successfully loaded bounding box data from ./combined_data\lapwing\texts\bounding_boxes.json
+2025-08-02 14:47:18.375 | INFO     | __main__:load_evaluation_data:103 - Successfully loaded image mapping. Image directory: ./combined_data\lapwing\images
+2025-08-02 14:47:18.397 | INFO     | __main__:load_evaluation_data:151 - Loaded and merged data for 28 prompts.
+2025-08-02 14:47:37.979 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'suspecious', Criterion:Alignment, Ranks:{'w_o_HitL': 4, 'Ours': 1, 'w_o_Tuning': 5, 'LLM-based': 1, 'w_o_Proto_Loss': 1}, Orders:['w_o_HitL', 'Ours', 'w_o_Tuning', 'LLM-based', 'w_o_Proto_Loss'], 
+2025-08-02 14:47:37.979 | INFO     | __main__:validate_and_navigate:410 - Saved absolute scores for P:P99, Prompt:'suspecious', Best Score:6, Worst Score:2
+2025-08-02 14:47:48.661 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'suspecious', Criterion:Naturalness, Ranks:{'w_o_HitL': 5, 'Ours': 1, 'LLM-based': 1, 'w_o_Proto_Loss': 1, 'w_o_Tuning': 4}, Orders:['w_o_HitL', 'Ours', 'LLM-based', 'w_o_Proto_Loss', 'w_o_Tuning'], 

logs/evaluation_ui_log_2025-08-02_14-51-10_704186.log

@@ -0,0 +1,7 @@
+2025-08-02 14:51:30.272 | INFO     | __main__:load_bbox_json:49 - Successfully loaded bounding box data from ./combined_data\lapwing\texts\bounding_boxes.json
+2025-08-02 14:51:30.273 | INFO     | __main__:load_evaluation_data:103 - Successfully loaded image mapping. Image directory: ./combined_data\lapwing\images
+2025-08-02 14:51:30.276 | INFO     | __main__:load_evaluation_data:151 - Loaded and merged data for 28 prompts.
+2025-08-02 14:51:45.724 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'annoyed', Criterion:Alignment, Ranks:{'LLM-based': 5, 'w_o_Proto_Loss': 1, 'w_o_HitL': 4, 'Ours': 2, 'w_o_Tuning': 3}, Orders:['LLM-based', 'w_o_Proto_Loss', 'w_o_HitL', 'Ours', 'w_o_Tuning'], 
+2025-08-02 14:51:45.725 | INFO     | __main__:validate_and_navigate:410 - Saved absolute scores for P:P99, Prompt:'annoyed', Best Score:6, Worst Score:2
+2025-08-02 14:52:06.249 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'annoyed', Criterion:Naturalness, Ranks:{'w_o_Proto_Loss': 2, 'Ours': 1, 'w_o_HitL': 4, 'LLM-based': 3, 'w_o_Tuning': 5}, Orders:['w_o_Proto_Loss', 'Ours', 'w_o_HitL', 'LLM-based', 'w_o_Tuning'], 
+2025-08-02 14:52:18.331 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'annoyed', Criterion:Attractiveness, Ranks:{'w_o_Tuning': 4, 'w_o_Proto_Loss': 2, 'w_o_HitL': 3, 'LLM-based': 5, 'Ours': 1}, Orders:['w_o_Tuning', 'w_o_Proto_Loss', 'w_o_HitL', 'LLM-based', 'Ours'], 

logs/evaluation_ui_log_2025-08-02_14-55-09_654842.log

@@ -0,0 +1,7 @@
+2025-08-02 14:55:20.980 | INFO     | __main__:load_bbox_json:49 - Successfully loaded bounding box data from ./combined_data\lapwing\texts\bounding_boxes.json
+2025-08-02 14:55:20.981 | INFO     | __main__:load_evaluation_data:103 - Successfully loaded image mapping. Image directory: ./combined_data\lapwing\images
+2025-08-02 14:55:20.983 | INFO     | __main__:load_evaluation_data:151 - Loaded and merged data for 28 prompts.
+2025-08-02 14:55:39.663 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'disgusted', Criterion:Alignment, Ranks:{'Ours': 1, 'w_o_HitL': 2, 'LLM-based': 3, 'w_o_Proto_Loss': 5, 'w_o_Tuning': 4}, Orders:['Ours', 'w_o_HitL', 'LLM-based', 'w_o_Proto_Loss', 'w_o_Tuning'], 
+2025-08-02 14:55:39.664 | INFO     | __main__:validate_and_navigate:410 - Saved absolute scores for P:P99, Prompt:'disgusted', Best Score:6, Worst Score:2
+2025-08-02 14:55:55.613 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'disgusted', Criterion:Naturalness, Ranks:{'LLM-based': 2, 'w_o_Proto_Loss': 4, 'w_o_HitL': 5, 'w_o_Tuning': 3, 'Ours': 1}, Orders:['LLM-based', 'w_o_Proto_Loss', 'w_o_HitL', 'w_o_Tuning', 'Ours'], 
+2025-08-02 14:56:07.162 | INFO     | __main__:validate_and_navigate:403 - Saved rank for P:P99, Prompt:'disgusted', Criterion:Attractiveness, Ranks:{'Ours': 1, 'w_o_HitL': 4, 'w_o_Tuning': 2, 'w_o_Proto_Loss': 5, 'LLM-based': 3}, Orders:['Ours', 'w_o_HitL', 'w_o_Tuning', 'w_o_Proto_Loss', 'LLM-based'], 

logs/evaluation_ui_log_2025-08-02_15-00-37_160749.log

@@ -0,0 +1,18 @@
+2025-08-02 15:00:54.581 | INFO     | __main__:load_bbox_json:49 - Successfully loaded bounding box data from ./combined_data\lapwing\texts\bounding_boxes.json
+2025-08-02 15:00:54.581 | INFO     | __main__:load_evaluation_data:103 - Successfully loaded image mapping. Image directory: ./combined_data\lapwing\images
+2025-08-02 15:00:54.583 | INFO     | __main__:load_evaluation_data:151 - Loaded and merged data for 28 prompts.
+2025-08-02 15:01:34.620 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'empty', Criterion:Alignment, Ranks:{'Ours': 3, 'w_o_Tuning': 5, 'w_o_Proto_Loss': 3, 'LLM-based': 1, 'w_o_HitL': 2}, Orders:['Ours', 'w_o_Tuning', 'w_o_Proto_Loss', 'LLM-based', 'w_o_HitL'], 
+2025-08-02 15:01:34.621 | INFO     | __main__:validate_and_navigate:418 - Saved absolute scores for P:P99, Prompt:'empty', Best Score:6, Worst Score:2
+2025-08-02 15:01:47.160 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'empty', Criterion:Naturalness, Ranks:{'w_o_Proto_Loss': 1, 'Ours': 1, 'LLM-based': 3, 'w_o_Tuning': 5, 'w_o_HitL': 4}, Orders:['w_o_Proto_Loss', 'Ours', 'LLM-based', 'w_o_Tuning', 'w_o_HitL'], 
+2025-08-02 15:01:58.405 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'empty', Criterion:Attractiveness, Ranks:{'LLM-based': 3, 'w_o_Tuning': 4, 'w_o_HitL': 5, 'Ours': 2, 'w_o_Proto_Loss': 1}, Orders:['LLM-based', 'w_o_Tuning', 'w_o_HitL', 'Ours', 'w_o_Proto_Loss'], 
+2025-08-02 15:02:26.776 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'hate', Criterion:Alignment, Ranks:{'w_o_Proto_Loss': 3, 'w_o_HitL': 1, 'w_o_Tuning': 2, 'Ours': 3, 'LLM-based': 5}, Orders:['w_o_Proto_Loss', 'w_o_HitL', 'w_o_Tuning', 'Ours', 'LLM-based'], 
+2025-08-02 15:02:26.776 | INFO     | __main__:validate_and_navigate:418 - Saved absolute scores for P:P99, Prompt:'hate', Best Score:6, Worst Score:2
+2025-08-02 15:02:36.858 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'hate', Criterion:Naturalness, Ranks:{'LLM-based': 4, 'w_o_HitL': 3, 'w_o_Tuning': 5, 'w_o_Proto_Loss': 1, 'Ours': 1}, Orders:['LLM-based', 'w_o_HitL', 'w_o_Tuning', 'w_o_Proto_Loss', 'Ours'], 
+2025-08-02 15:02:50.653 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'hate', Criterion:Attractiveness, Ranks:{'w_o_Tuning': 4, 'Ours': 2, 'LLM-based': 5, 'w_o_Proto_Loss': 2, 'w_o_HitL': 1}, Orders:['w_o_Tuning', 'Ours', 'LLM-based', 'w_o_Proto_Loss', 'w_o_HitL'], 
+2025-08-02 15:03:06.892 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'contempt', Criterion:Alignment, Ranks:{'LLM-based': 2, 'w_o_HitL': 4, 'w_o_Proto_Loss': 5, 'Ours': 3, 'w_o_Tuning': 1}, Orders:['LLM-based', 'w_o_HitL', 'w_o_Proto_Loss', 'Ours', 'w_o_Tuning'], 
+2025-08-02 15:03:06.892 | INFO     | __main__:validate_and_navigate:418 - Saved absolute scores for P:P99, Prompt:'contempt', Best Score:6, Worst Score:2
+2025-08-02 15:03:19.231 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'contempt', Criterion:Naturalness, Ranks:{'w_o_Tuning': 1, 'w_o_HitL': 3, 'Ours': 5, 'LLM-based': 2, 'w_o_Proto_Loss': 5}, Orders:['w_o_Tuning', 'w_o_HitL', 'Ours', 'LLM-based', 'w_o_Proto_Loss'], 
+2025-08-02 15:03:35.775 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'contempt', Criterion:Attractiveness, Ranks:{'w_o_HitL': 1, 'LLM-based': 3, 'w_o_Proto_Loss': 5, 'w_o_Tuning': 2, 'Ours': 5}, Orders:['w_o_HitL', 'LLM-based', 'w_o_Proto_Loss', 'w_o_Tuning', 'Ours'], 
+2025-08-02 15:04:01.160 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'fun', Criterion:Alignment, Ranks:{'w_o_Proto_Loss': 3, 'w_o_HitL': 4, 'Ours': 2, 'LLM-based': 1, 'w_o_Tuning': 5}, Orders:['w_o_Proto_Loss', 'w_o_HitL', 'Ours', 'LLM-based', 'w_o_Tuning'], 
+2025-08-02 15:04:01.161 | INFO     | __main__:validate_and_navigate:418 - Saved absolute scores for P:P99, Prompt:'fun', Best Score:6, Worst Score:2
+2025-08-02 15:04:14.325 | INFO     | __main__:validate_and_navigate:410 - Saved rank for P:P99, Prompt:'fun', Criterion:Naturalness, Ranks:{'Ours': 1, 'w_o_Proto_Loss': 3, 'w_o_Tuning': 4, 'LLM-based': 2, 'w_o_HitL': 5}, Orders:['Ours', 'w_o_Proto_Loss', 'w_o_Tuning', 'LLM-based', 'w_o_HitL'], 

results/P16/LLM-based/P16_LLM-based_all_predictions.jsonl

@@ -0,0 +1,28 @@
+{"participant_id": "P16", "condition": "LLM-based", "text_prompt": "happy", "prompt_category": "basic_emotion", "prediction": {"blendshape_names": {"Eyes": "笑い", "Eye Brow": "にこり"}, "blendshape_index": {"0": 1, "1": 3}, "blendshape_confidence": {"0": 1.0, "1": 1.0}}}
+{"participant_id": "P16", "condition": "LLM-based", "text_prompt": "sad", "prompt_category": "basic_emotion", "prediction": {"blendshape_names": {"Eyes": "なごみ", "Eye Brow": "困る"}, "blendshape_index": {"0": 2, "1": 1}, "blendshape_confidence": {"0": 1.0, "1": 1.0}}}
+{"participant_id": "P16", "condition": "LLM-based", "text_prompt": "angry", "prompt_category": "basic_emotion", "prediction": {"blendshape_names": {"Eyes": "じと目", "Eye Brow": "怒り"}, "blendshape_index": {"0": 4, "1": 2}, "blendshape_confidence": {"0": 1.0, "1": 1.0}}}
+{"participant_id": "P16", "condition": "LLM-based", "text_prompt": "surprised", "prompt_category": "basic_emotion", "prediction": {"blendshape_names": {"Eyes": "びっくり", "Eye Brow": "上"}, "blendshape_index": {"0": 3, "1": 4}, "blendshape_confidence": {"0": 1.0, "1": 1.0}}}
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results/P16/Ours/P16_Ours_all_predictions.jsonl

@@ -0,0 +1,28 @@
+{"participant_id": "P16", "condition": "Ours", "text_prompt": "happy", "prompt_category": "basic_emotion", "prediction": {"blendshape_names": {"Eyes": "none", "Eye Brow": "真面目"}, "blendshape_index": {"0": -1, "1": 0}, "blendshape_confidence": {"0": 0.9492596983909607, "1": 0.6670171022415161}}}
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results/P16/w_o_HitL/P16_w_o_HitL_all_predictions.jsonl

@@ -0,0 +1,28 @@
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results/P16/w_o_Proto_Loss/P16_w_o_Proto_Loss_all_predictions.jsonl

@@ -0,0 +1,28 @@
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results/P16/w_o_Tuning/P16_w_o_Tuning_all_predictions.jsonl

@@ -0,0 +1,28 @@
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