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app.py

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+import gradio as gr
+import os
+import random
+import uuid
+import csv
+from datetime import datetime
+from pathlib import Path
+from huggingface_hub import CommitScheduler
+
+# --- 1. 配置区域 ---
+
+# 你的数据集地址 (已修改)
+DATASET_REPO_ID = "Emilyxml/moveit"
+
+# 数据源文件夹 (读取你的图片和txt)
+DATA_FOLDER = "data"
+
+# 临时日志文件夹 (用于存放用户生成的CSV，Scheduler 会监控这里)
+LOG_FOLDER = Path("logs")
+LOG_FOLDER.mkdir(parents=True, exist_ok=True)
+
+# 获取 Token (需要在 Space 设置里配置 HF_TOKEN)
+TOKEN = os.environ.get("HF_TOKEN")
+
+# --- 2. 启动同步调度器 ---
+# 只要 logs 文件夹里有 CSV 变化，就自动上传到 Dataset 的 data 文件夹下
+scheduler = CommitScheduler(
+    repo_id=DATASET_REPO_ID,
+    repo_type="dataset",
+    folder_path=LOG_FOLDER, # 监控本地的 logs 文件夹
+    path_in_repo="data",    # 上传到 Dataset 的 data 目录中
+    every=1,                # 每分钟同步一次
+    token=TOKEN
+)
+
+# --- 3. 数据加载逻辑 ---
+def load_data():
+    groups = {}
+    
+    # 检查 data 文件夹是否存在
+    if not os.path.exists(DATA_FOLDER):
+        # 如果不存在，尝试创建（防止报错），但实际应该由你上传文件
+        os.makedirs(DATA_FOLDER, exist_ok=True)
+        print(f"Warning: {DATA_FOLDER} not found. Please upload your images.")
+        return {}, []
+
+    # 遍历文件
+    for filename in os.listdir(DATA_FOLDER):
+        if filename.startswith('.'): continue # 跳过隐藏文件
+        
+        file_path = os.path.join(DATA_FOLDER, filename)
+        prefix = filename[:5] # 以前5个字符作为组ID
+        
+        if prefix not in groups:
+            groups[prefix] = {"images": [], "instruction": "暂无说明"}
+
+        # 识别图片
+        if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.bmp')):
+            groups[prefix]["images"].append(file_path)
+        # 识别文本
+        elif filename.lower().endswith('.txt'):
+            try:
+                with open(file_path, "r", encoding="utf-8") as f:
+                    groups[prefix]["instruction"] = f.read()
+            except:
+                # 兼容 gbk 编码
+                with open(file_path, "r", encoding="gbk") as f:
+                    groups[prefix]["instruction"] = f.read()
+
+    # 过滤掉没有图片的组
+    valid_groups = {k: v for k, v in groups.items() if len(v["images"]) > 0}
+    
+    # 生成题目列表，并随机打乱
+    group_ids = list(valid_groups.keys())
+    random.shuffle(group_ids)
+    
+    print(f"Loaded {len(group_ids)} groups of images.")
+    return valid_groups, group_ids
+
+# 全局加载数据
+ALL_GROUPS, ALL_GROUP_IDS = load_data()
+
+# --- 4. 保存逻辑 (每个用户一个独立CSV) ---
+def save_user_vote(user_id, group_id, choice_label, method_name):
+    """
+    保存单次投票到 logs/user_{user_id}.csv
+    """
+    user_filename = f"user_{user_id}.csv"
+    user_file_path = LOG_FOLDER / user_filename
+    
+    # 数据行
+    row = [
+        user_id,
+        datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        group_id,
+        choice_label,  # 用户选了 Option A 还是 B
+        method_name    # 真实的方法名
+    ]
+    
+    # 线程安全写入
+    with scheduler.lock:
+        file_exists = user_file_path.exists()
+        with user_file_path.open("a", newline="", encoding="utf-8") as f:
+            writer = csv.writer(f)
+            # 如果是新文件，先写表头
+            if not file_exists:
+                writer.writerow(["user_id", "timestamp", "group_id", "selected_label", "selected_method"])
+            writer.writerow(row)
+    
+    print(f"Saved vote for {user_id}: {method_name}")
+
+# --- 5. 交互逻辑 ---
+def get_next_question(user_state):
+    current_idx = user_state["index"]
+    
+    # 1. 检查是否做完
+    if current_idx >= len(ALL_GROUP_IDS):
+        return (
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(value="## 🎉 测试结束！\n感谢您的参与，您的选择已保存。", visible=True),
+            user_state,
+            []
+        )
+    
+    # 2. 获取当前组
+    group_id = ALL_GROUP_IDS[current_idx]
+    group_data = ALL_GROUPS[group_id]
+    
+    # 3. 准备 Prompt
+    instruction_text = f"## 任务 ({current_idx + 1} / {len(ALL_GROUP_IDS)})\n\n{group_data['instruction']}"
+    
+    # 4. 准备图片 (打乱顺序实现盲测)
+    original_images = group_data["images"]
+    shuffled_images = original_images.copy()
+    random.shuffle(shuffled_images)
+    
+    # 构造 Gradio 显示对象
+    display_list = []
+    for i, img_path in enumerate(shuffled_images):
+        label = f"Option {chr(65+i)}" # Option A, Option B...
+        display_list.append((img_path, label))
+        
+    return (
+        gr.update(value=instruction_text, visible=True),
+        gr.update(value=display_list, visible=True),
+        gr.update(visible=True),
+        gr.update(visible=False),
+        user_state,
+        shuffled_images # 将乱序后的真实路径列表传给 State
+    )
+
+def on_vote(user_state, current_file_paths, select_data: gr.SelectData = None, is_none=False):
+    user_id = user_state["user_id"]
+    current_idx = user_state["index"]
+    
+    # 防止溢出
+    if current_idx >= len(ALL_GROUP_IDS):
+        return get_next_question(user_state)
+        
+    group_id = ALL_GROUP_IDS[current_idx]
+    selected_method = "Unknown"
+    selected_label = "None"
+    
+    # --- 解析选择 ---
+    if is_none:
+        selected_method = "None_Satisfied"
+        selected_label = "Rejected All"
+    elif select_data is not None:
+        idx = select_data.index
+        # 获取真实路径
+        real_image_path = current_file_paths[idx]
+        selected_label = select_data.value["caption"]
+        
+        # 提取方法名 (例如 6180a_omnigen.png -> omnigen)
+        filename = os.path.basename(real_image_path)
+        name_no_ext = os.path.splitext(filename)[0]
+        parts = name_no_ext.split('_', 1)
+        if len(parts) > 1:
+            selected_method = parts[1]
+        else:
+            selected_method = name_no_ext
+            
+    # --- 保存 ---
+    save_user_vote(user_id, group_id, selected_label, selected_method)
+    
+    # --- 下一题 ---
+    user_state["index"] += 1
+    return get_next_question(user_state)
+
+# --- 6. 界面构建 ---
+with gr.Blocks(title="User Study - MoveIt") as demo:
+    # State 初始化：每次刷新网页生成新的 user_id
+    state_user = gr.State(lambda: {"user_id": str(uuid.uuid4())[:8], "index": 0})
+    state_files = gr.State([])
+    
+    with gr.Column(elem_id="main"):
+        instruction_md = gr.Markdown("Loading...")
+        
+        gallery = gr.Gallery(
+            label="请点击选择最佳图片",
+            columns=[2],
+            height="auto",
+            interactive=True
+        )
+        
+        btn_none = gr.Button("🚫 没有任何一张图片符合要求", variant="stop")
+        
+        end_msg = gr.Markdown(visible=False)
+
+    # 事件绑定
+    demo.load(fn=get_next_question, inputs=[state_user], outputs=[instruction_md, gallery, btn_none, end_msg, state_user, state_files])
+    
+    gallery.select(fn=lambda s, f, evt: on_vote(s, f, evt, is_none=False), inputs=[state_user, state_files], outputs=[instruction_md, gallery, btn_none, end_msg, state_user, state_files])
+    
+    btn_none.click(fn=lambda s, f: on_vote(s, f, None, is_none=True), inputs=[state_user, state_files], outputs=[instruction_md, gallery, btn_none, end_msg, state_user, state_files])
+
+if __name__ == "__main__":
+    demo.launch()

data/02629.txt

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+move the watercolor pens to the right of the the white suitcase.

data/07ddc.txt

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+move the blue frisbee to the left of the the binder clips box.

data/1bcdc.txt

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+move the watercolor pens to the top of the the pink suitcase.

data/261b7.txt

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+Place the white box to the right side of the red square.

data/26718.txt

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+Move the silver remote control from the right of the black game console to the left of the black game console.