Add application file

app.py

@@ -0,0 +1,334 @@
+import gradio as gr
+import os
+import json
+from datetime import datetime
+from datasets import load_dataset
+import random
+
+# 全局变量存储数据集
+DATASET = None
+VIDEO_DATA = None
+
+# 从Hugging Face dataset加载视频
+def load_videos_from_huggingface():
+    global DATASET, VIDEO_DATA
+    
+    try:
+        print("正在加载数据集: WenjiaWang/videoforuser...")
+        DATASET = load_dataset("WenjiaWang/videoforuser", split="train")
+        print(f"成功加载数据集，共 {len(DATASET)} 个视频")
+        
+        # 组织视频数据：按场景分组
+        VIDEO_DATA = {}
+        
+        for idx, item in enumerate(DATASET):
+            # 获取视频路径信息
+            if 'video' in item:
+                video_path = item['video']
+            elif 'path' in item:
+                video_path = item['path']
+            else:
+                print(f"警告: 第 {idx} 项没有视频路径字段")
+                continue
+            
+            # 从路径中提取场景名和方法名
+            # 假设路径格式类似: "videos/scene_name/method.mp4"
+            path_parts = video_path.split('/')
+            if len(path_parts) >= 2:
+                scene_name = path_parts[-2]  # 倒数第二部分是场景名
+                file_name = path_parts[-1]    # 最后部分是文件名
+                
+                # 提取方法名
+                method_name = file_name.replace('.mp4', '')
+                
+                if scene_name not in VIDEO_DATA:
+                    VIDEO_DATA[scene_name] = {}
+                
+                # 存储视频信息（包括在dataset中的索引）
+                VIDEO_DATA[scene_name][method_name] = {
+                    'index': idx,
+                    'path': video_path,
+                    'item': item
+                }
+        
+        print(f"组织完成，共 {len(VIDEO_DATA)} 个场景")
+        return True
+        
+    except Exception as e:
+        print(f"加载数据集失败: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+# 获取所有场景列表
+def get_question_folders():
+    if VIDEO_DATA is None:
+        success = load_videos_from_huggingface()
+        if not success:
+            return []
+    
+    return sorted(list(VIDEO_DATA.keys()))
+
+# 获取某个场景的所有视频
+def get_videos_for_question(scene_name):
+    if VIDEO_DATA is None or scene_name not in VIDEO_DATA:
+        return {}, {}
+    
+    scene_videos = VIDEO_DATA[scene_name]
+    
+    # 创建方法名到真实名称的映射
+    method_names = list(scene_videos.keys())
+    
+    # 随机打乱顺序以匿名化
+    shuffled_methods = method_names.copy()
+    random.shuffle(shuffled_methods)
+    
+    videos = {}
+    method_mapping = {}
+    
+    for i, method_name in enumerate(shuffled_methods):
+        display_name = f"Method {chr(65+i)}"  # Method A, B, C, D
+        
+        # 获取视频数据
+        video_info = scene_videos[method_name]
+        video_item = video_info['item']
+        
+        # 从dataset item中获取视频文件
+        if 'video' in video_item:
+            videos[display_name] = video_item['video']  # 这应该是视频文件路径或对象
+        
+        method_mapping[display_name] = method_name
+    
+    return videos, method_mapping
+
+# 保存评分数据
+def save_ratings(scene_name, ratings_data, method_mapping):
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    
+    # 将显示名称映射到真实方法名
+    mapped_ratings = {}
+    for display_name, ratings in ratings_data.items():
+        real_method = method_mapping.get(display_name, display_name)
+        mapped_ratings[real_method] = ratings
+    
+    # 读取现有数据
+    all_data = []
+    if os.path.exists("ratings_data.json"):
+        try:
+            with open("ratings_data.json", "r", encoding="utf-8") as f:
+                all_data = json.load(f)
+        except:
+            all_data = []
+    
+    # 添加新数据
+    entry = {
+        "timestamp": timestamp,
+        "scene": scene_name,
+        "ratings": mapped_ratings
+    }
+    all_data.append(entry)
+    
+    # 保存数据
+    with open("ratings_data.json", "w", encoding="utf-8") as f:
+        json.dump(all_data, f, ensure_ascii=False, indent=2)
+    
+    return f"✓ 评分已保存 / Ratings saved"
+
+# 创建Gradio界面
+def create_video_survey_app():
+    # 预加载数据集
+    print("初始化应用...")
+    load_videos_from_huggingface()
+    question_folders = get_question_folders()
+    
+    if not question_folders:
+        print("错误: 没有找到任何场景数据")
+        return None
+    
+    print(f"找到 {len(question_folders)} 个场景")
+    
+    with gr.Blocks(title="视频生成质量用户研究", theme=gr.themes.Soft()) as demo:
+        gr.Markdown("# 🎬 视频生成质量用户研究 / Video Generation Quality User Study")
+        gr.Markdown("""
+        ### 说明 / Instructions:
+        - ��观看每个视频并进行评分 / Please watch each video and rate them
+        - 评分标准 / Rating criteria:
+          - **动态生成质量** / Dynamic Generation Quality: 视频中物体运动的流畅性和真实性
+          - **静态一致性** / Static Consistency: 视频中静态物体的稳定性和一致性
+          - **整体质量** / Overall Quality: 视频的整体观感
+        - 评分范围：1-5分（5分最好）/ Rating scale: 1-5 (5 = Best)
+        """)
+        
+        # 状态变量
+        current_question_idx = gr.State(0)
+        current_method_mapping = gr.State({})
+        
+        # 进度显示
+        with gr.Row():
+            prev_btn = gr.Button("⬅️ 上一题 / Previous", size="sm")
+            question_text = gr.Markdown(f"**场景 1 / {len(question_folders)}**")
+            next_btn = gr.Button("下一题 / Next ➡️", size="sm", variant="primary")
+        
+        status_text = gr.Textbox(label="状态 / Status", interactive=False, visible=False)
+        
+        # 视频显示区域（4个视频）
+        video_components = []
+        rating_components = []
+        
+        for i in range(4):
+            method_name = f"Method {chr(65+i)}"
+            
+            with gr.Group():
+                gr.Markdown(f"### 🎥 {method_name}")
+                
+                video = gr.Video(label="", height=300)
+                video_components.append(video)
+                
+                with gr.Row():
+                    dynamic = gr.Slider(
+                        minimum=1, maximum=5, step=1, value=3,
+                        label="动态质量 / Dynamic Quality",
+                        info="1=差 / Poor, 5=优秀 / Excellent"
+                    )
+                    static = gr.Slider(
+                        minimum=1, maximum=5, step=1, value=3,
+                        label="静态一致性 / Static Consistency",
+                        info="1=差 / Poor, 5=优秀 / Excellent"
+                    )
+                    overall = gr.Slider(
+                        minimum=1, maximum=5, step=1, value=3,
+                        label="整体质量 / Overall Quality",
+                        info="1=差 / Poor, 5=优秀 / Excellent"
+                    )
+                
+                rating_components.append({
+                    "dynamic": dynamic,
+                    "static": static,
+                    "overall": overall
+                })
+        
+        # 更新问题显示
+        def update_question(question_idx, save_previous=False, prev_ratings=None, prev_mapping=None):
+            if question_idx < 0:
+                question_idx = 0
+            if question_idx >= len(question_folders):
+                question_idx = len(question_folders) - 1
+            
+            # 如果需要，保存上一题的评分
+            save_msg = ""
+            if save_previous and prev_ratings and prev_mapping:
+                prev_scene = question_folders[question_idx - 1] if question_idx > 0 else None
+                if prev_scene:
+                    save_msg = save_ratings(prev_scene, prev_ratings, prev_mapping)
+            
+            scene_name = question_folders[question_idx]
+            videos, method_mapping = get_videos_for_question(scene_name)
+            
+            # 更新视频显示
+            video_updates = []
+            for i in range(4):
+                method_name = f"Method {chr(65+i)}"
+                if method_name in videos:
+                    video_updates.append(gr.Video(value=videos[method_name], visible=True))
+                else:
+                    video_updates.append(gr.Video(value=None, visible=False))
+            
+            # 重置评分
+            rating_updates = [gr.Slider(value=3) for _ in range(12)]  # 4个视频 x 3个评分
+            
+            question_markdown = f"**场景 {question_idx + 1} / {len(question_folders)}**: `{scene_name}`"
+            
+            return (
+                [question_idx, method_mapping, question_markdown, save_msg] +
+                video_updates +
+                rating_updates
+            )
+        
+        # 收集当前评分
+        def collect_ratings(*rating_values):
+            ratings = {}
+            for i in range(4):
+                method_name = f"Method {chr(65+i)}"
+                base_idx = i * 3
+                ratings[method_name] = {
+                    "dynamic_quality": rating_values[base_idx],
+                    "static_consistency": rating_values[base_idx + 1],
+                    "overall_quality": rating_values[base_idx + 2]
+                }
+            return ratings
+        
+        # 下一题按钮
+        def on_next(question_idx, method_mapping, *rating_values):
+            # 收集当前评分
+            current_ratings = collect_ratings(*rating_values)
+            
+            # 保存当前评分
+            scene_name = question_folders[question_idx]
+            save_msg = save_ratings(scene_name, current_ratings, method_mapping)
+            
+            # 移动到下一题
+            new_idx = question_idx + 1
+            if new_idx >= len(question_folders):
+                return [
+                    question_idx,
+                    method_mapping,
+                    f"**✅ 所有场景已完成！/ All scenes completed!**",
+                    save_msg + "\n🎉 感谢参与！/ Thank you for participating!"
+                ] + [gr.Video()] * 4 + [gr.Slider(value=3)] * 12
+            
+            return update_question(new_idx)
+        
+        # 上一题按钮
+        def on_prev(question_idx, *args):
+            new_idx = question_idx - 1
+            if new_idx < 0:
+                new_idx = 0
+            return update_question(new_idx)
+        
+        # 收集所有评分组件
+        all_rating_inputs = []
+        for comp in rating_components:
+            all_rating_inputs.extend([comp["dynamic"], comp["static"], comp["overall"]])
+        
+        # 绑定事件
+        next_btn.click(
+            on_next,
+            inputs=[current_question_idx, current_method_mapping] + all_rating_inputs,
+            outputs=[
+                current_question_idx,
+                current_method_mapping,
+                question_text,
+                status_text
+            ] + video_components + all_rating_inputs
+        )
+        
+        prev_btn.click(
+            on_prev,
+            inputs=[current_question_idx] + all_rating_inputs,
+            outputs=[
+                current_question_idx,
+                current_method_mapping,
+                question_text,
+                status_text
+            ] + video_components + all_rating_inputs
+        )
+        
+        # 初始化第一个问题
+        demo.load(
+            lambda: update_question(0),
+            outputs=[
+                current_question_idx,
+                current_method_mapping,
+                question_text,
+                status_text
+            ] + video_components + all_rating_inputs
+        )
+    
+    return demo
+
+if __name__ == "__main__":
+    app = create_video_survey_app()
+    if app:
+        app.launch(server_name="0.0.0.0", server_port=7860, share=False)
+    else:
+        print("应用初始化失败 / App initialization failed")