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+data/f2c9d_step1xv11.png filter=lfs diff=lfs merge=lfs -text +data/f3099_Flux.png filter=lfs diff=lfs merge=lfs -text +data/f3099_magic_brush.png filter=lfs diff=lfs merge=lfs -text +data/f3099_my-before.png filter=lfs diff=lfs merge=lfs -text +data/f3099_my.png filter=lfs diff=lfs merge=lfs -text +data/f3099_omnigen2.png filter=lfs diff=lfs merge=lfs -text +data/f3099_origin.png filter=lfs diff=lfs merge=lfs -text +data/f3099_qwen.png filter=lfs diff=lfs merge=lfs -text +data/f3099_step1x-v1.png filter=lfs diff=lfs merge=lfs -text +data/f3099_step1xv11.png filter=lfs diff=lfs merge=lfs -text diff --git a/app.py b/app.py new file mode 100644 index 0000000000000000000000000000000000000000..210e2eaab707eab75cdc304169393f45f95337fe --- /dev/null +++ b/app.py @@ -0,0 +1,220 @@ +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() diff --git a/data/02629.txt b/data/02629.txt new file mode 100644 index 0000000000000000000000000000000000000000..c6eb4d310875e64d37efe5a0043c21050bbc382c --- /dev/null +++ b/data/02629.txt @@ -0,0 +1 @@ +move the watercolor pens to the right of the the white suitcase. \ No newline at end of file diff --git a/data/02629_Flux.png b/data/02629_Flux.png new file mode 100644 index 0000000000000000000000000000000000000000..456096ccfd4e507a5c51abcddfe1b8845f71475a --- /dev/null +++ b/data/02629_Flux.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f23e12deadfceecbbea3327b2e00e8ad47d3ac4e08b660267e17147a0462e7d3 +size 6594094 diff --git a/data/02629_magic_brush.png b/data/02629_magic_brush.png new file mode 100644 index 0000000000000000000000000000000000000000..3fc18e29090075fb1fa13a68f6ed41ce7f142753 --- /dev/null +++ b/data/02629_magic_brush.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 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