Upload app.py

app.py

@@ -53,7 +53,7 @@ def eval_request(model_name, org_link, huggingface_data_set_name):
     }
     response = requests.post(
         "http://47.239.99.255/A2Bench_evaluation/eval",
-        json=params,  # 使用json参数自动设置Content-Type为application/json
+        params=params,  # 使用json参数自动设置Content-Type为application/json
         headers={"Content-Type": "application/json"}
     )
     return response.json()
@@ -97,7 +97,6 @@ _HEADER_1 = '''
     <h1 style="font-size: 2.5rem; font-weight: 700; margin-bottom: 1rem; display: contents;">A2-Bench Leaderboard</h1>
     <p style="font-size: 1rem; margin-bottom: 1.5rem;">Paper: <a href='https://arxiv.org/pdf/2504.02436' target='_blank'>SkyReels-A2 </a> | Codes: <a href='https://github.com/SkyworkAI/SkyReels-A2' target='_blank'>GitHub</a> | <a href='https://huggingface.co/Skywork/SkyReels-A2' target='_blank'>HugginceFace</a></p> 
 </div>
-
 ❗️❗️❗️**LEADERBOARD INTRODUCTION:** ❗️❗️❗️  
 This is A2-Bench leaderboard which is used to evaluate the performance of elements-to-video (E2V) generation models.  
 We provide an evaluation set containing 50 paired multiple elements (character, object, and background). You can check [evaluation set introduction]() for more details. Each evaluation case includes:
@@ -122,15 +121,12 @@ img = '''
 </div>
 '''
 __HEADER__2 = '''
-
 We provide a set of evaluation metric of elements-to-video models and a leaderboard to show the performance of different models. 
 Evaluation metric include:
 - Elements Consistency: Measures character id consistency using arcface human recognition model, and measures object and background consistency using CLIP model.
 - Video Quality: Measures video quality on image quality, dynamic degree, aesthetic quality and motion smoothness.
 - T2V Metrics: Measures text-video consistency using CLIP 
-
 You can check [Metric Introduction](https://skyworkai.github.io/skyreels-a2.github.io/static/images/bench.png) for more details.
-
 The leaderboard ranks the models based on the comprehensive score, which is the weighted average of all the metrics. We give T2V metrics and object consistency metrics higher weights. 
 You can click the model name to visit the project page, At meantime, you can upload your model result as a huggingface dataset like [this](https://huggingface.co/datasets/ColinYK/pika_dataset).
 '''  # noqa E501
@@ -138,7 +134,6 @@ You can click the model name to visit the project page, At meantime, you can upl
 _CITE_ = r"""
 If A2-Bench is helpful, please help to ⭐ the <a href='https://github.com/SkyworkAI/SkyReels-A2' target='_blank'> Github Repo</a>. Thanks!
 ---
-
 📧 **Contact**
 If you have any questions or feedbacks, feel free to open a discussion or contact <b>[email protected]</b>.
 """  # noqa E501
@@ -186,4 +181,4 @@ with gr.Blocks(css=".gr-dataframe a {text-decoration: none; color: inherit;}")
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()