Update app.py

app.py

@@ -22,113 +22,6 @@ def upload_file(files):
     file_paths = [file.name for file in files]
     return file_paths
 
-def add_new_eval(
-    input_file,
-    model_name_textbox: str,
-    revision_name_textbox: str,
-    model_link: str,
-    team_name: str,
-    contact_email: str,
-    access_type: str,
-    model_publish: str,
-    model_resolution: str,
-    model_fps: str,
-    model_frame: str,
-    model_video_length: str,
-    model_checkpoint: str,
-    model_commit_id: str,
-    model_video_format: str
-):
-    if input_file is None:
-        return "Error! Empty file!"
-    if  model_link == '' or model_name_textbox == '' or contact_email == '':
-        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)
-    # upload_data=json.loads(input_file)
-    upload_content = input_file
-    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
-    submission_repo.git_pull()
-    filename = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-    
-    now = datetime.datetime.now()
-    update_time = now.strftime("%Y-%m-%d")  # Capture update time
-    with open(f'{SUBMISSION_NAME}/{filename}.zip','wb') as f:
-        f.write(input_file)
-    # shutil.copyfile(CSV_DIR, os.path.join(SUBMISSION_NAME, f"{input_file}"))
-
-    csv_data = pd.read_csv(CSV_DIR)
-
-    if revision_name_textbox == '':
-        col = csv_data.shape[0]
-        model_name = model_name_textbox.replace(',',' ')
-    else:
-        model_name = revision_name_textbox.replace(',',' ')
-        model_name_list = csv_data['Model Name (clickable)']
-        name_list = [name.split(']')[0][1:] for name in model_name_list]
-        if revision_name_textbox not in name_list:
-            col = csv_data.shape[0]
-        else:
-            col = name_list.index(revision_name_textbox)    
-    if model_link == '':
-        model_name = model_name  # no url
-    else:
-        model_name = '[' + model_name + '](' + model_link + ')'
-
-    os.makedirs(filename, exist_ok=True)
-    with zipfile.ZipFile(io.BytesIO(input_file), 'r') as zip_ref:
-        zip_ref.extractall(filename)
-
-    upload_data = {}
-    for file in os.listdir(filename):
-        if file.startswith('.') or file.startswith('__'):
-            print(f"Skip the file: {file}")
-            continue
-        cur_file = os.path.join(filename, file)
-        if os.path.isdir(cur_file):
-            for subfile in os.listdir(cur_file):
-                if subfile.endswith(".json"):
-                    with open(os.path.join(cur_file, subfile)) as ff:
-                        cur_json = json.load(ff)
-                        print(file, type(cur_json))
-                        if isinstance(cur_json, dict):
-                            print(cur_json.keys())
-                            for key in cur_json:
-                                upload_data[key.replace('_',' ')] = cur_json[key][0]
-                                print(f"{key}:{cur_json[key][0]}")
-        elif cur_file.endswith('json'):
-            with open(cur_file) as ff:
-                cur_json = json.load(ff)
-                print(file, type(cur_json))
-                if isinstance(cur_json, dict):
-                    print(cur_json.keys())
-                    for key in cur_json:
-                        upload_data[key.replace('_',' ')] = cur_json[key][0]
-                        print(f"{key}:{cur_json[key][0]}")
-    # add new data
-    new_data = [model_name]
-    print('upload_data:', upload_data)
-    for key in TASK_INFO:
-        if key in upload_data:
-            new_data.append(upload_data[key])
-        else:
-            new_data.append(0)
-    if team_name =='' or 'vbench' in team_name.lower():
-        new_data.append("User Upload")
-    else:
-        new_data.append(team_name)
-
-    new_data.append(contact_email.replace(',',' and ')) # Add contact email [private]
-    new_data.append(update_time)  # Add the update time
-    new_data.append(team_name)
-    new_data.append(access_type)
-
-    csv_data.loc[col] = new_data
-    csv_data = csv_data.to_csv(CSV_DIR, index=False)
-    with open(INFO_DIR,'a') as f:
-        f.write(f"{model_name}\t{update_time}\t{model_publish}\t{model_resolution}\t{model_fps}\t{model_frame}\t{model_video_length}\t{model_checkpoint}\t{model_commit_id}\t{model_video_format}\n")
-    submission_repo.push_to_hub()
-    print("success update", model_name)
-    return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
-
 def add_new_eval_i2v(
     input_file,
     model_name_textbox: str,
@@ -413,41 +306,6 @@ def get_baseline_df():
     df = convert_scores_to_percentage(df)
     return df
 
-def get_baseline_df_quality():
-    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
-    submission_repo.git_pull()
-    df = pd.read_csv(QUALITY_DIR)
-    df = get_final_score_quality(df, checkbox_group_quality.value)
-    df = df.sort_values(by="Selected Score", ascending=False)
-    present_columns = MODEL_INFO_TAB_QUALITY + checkbox_group_quality.value
-    df = df[present_columns]
-    df = convert_scores_to_percentage(df)
-    return df
-
-def get_baseline_df_i2v():
-    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
-    submission_repo.git_pull()
-    df = pd.read_csv(I2V_DIR)
-    df = get_final_score_i2v(df, checkbox_group_i2v.value)
-    df = df.sort_values(by="Selected Score", ascending=False)
-    present_columns = MODEL_INFO_TAB_I2V + checkbox_group_i2v.value
-    # df = df[df["Sampled by"] == 'VBench Team'] 
-    df = df[present_columns]
-    df = convert_scores_to_percentage(df)
-    return df
-
-def get_baseline_df_long():
-    submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
-    submission_repo.git_pull()
-    df = pd.read_csv(LONG_DIR)
-    df = get_final_score(df, checkbox_group.value)
-    df = df.sort_values(by="Selected Score", ascending=False)
-    present_columns = MODEL_INFO + checkbox_group.value
-    # df = df[df["Sampled by"] == 'VBench Team'] 
-    df = df[present_columns]
-    df = convert_scores_to_percentage(df)
-    return df
-
 def get_all_df(selected_columns, dir=CSV_DIR):
     submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
     submission_repo.git_pull()
@@ -673,215 +531,12 @@ with block:
             checkbox_group.change(fn=on_filter_model_size_method_change, inputs=[ checkbox_group, vbench_team_filter, vbench_validate_filter], outputs=data_component)
             vbench_team_filter.change(fn=on_filter_model_size_method_change, inputs=[checkbox_group, vbench_team_filter, vbench_validate_filter], outputs=data_component)
             vbench_validate_filter.change(fn=on_filter_model_size_method_change, inputs=[checkbox_group, vbench_team_filter, vbench_validate_filter], outputs=data_component)
-        # Table 1
-        with gr.TabItem("Video Quality", elem_id="vbench-tab-table", id=2):
-            with gr.Accordion("INSTRUCTION", open=False):
-                    citation_button = gr.Textbox(
-                        value=QUALITY_CLAIM_TEXT,
-                        label="",
-                        elem_id="quality-button",
-                        lines=2,
-                    )
-            with gr.Row():
-                with gr.Column(scale=1.0):
-                    # selection for column part:
-                    
-                    checkbox_group_quality = gr.CheckboxGroup(
-                        choices=QUALITY_TAB,
-                        value=QUALITY_TAB,
-                        label="Evaluation Quality Dimension",
-                        interactive=True,
-                    )
-
-            data_component_quality = gr.components.Dataframe(
-                value=get_baseline_df_quality, 
-                headers=COLUMN_NAMES_QUALITY,
-                type="pandas", 
-                datatype=DATA_TITILE_TYPE,
-                interactive=False,
-                visible=True,
-                )
-    
-            checkbox_group_quality.change(fn=on_filter_model_size_method_change_quality, inputs=[checkbox_group_quality], outputs=data_component_quality)
-        
-        # Table i2v
-        with gr.TabItem("VBench-I2V", elem_id="vbench-tab-table", id=3):
-            with gr.Accordion("NOTE", open=False):
-                    i2v_note_button = gr.Textbox(
-                        value=I2V_CLAIM_TEXT,
-                        label="",
-                        elem_id="quality-button",
-                        lines=3,
-                    )
-            with gr.Row():
-                with gr.Column(scale=1.0):
-                    # selection for column part:
-                    with gr.Row():
-                        vbench_team_filter_i2v = gr.Checkbox(
-                            label="Sampled by VBench Team (Uncheck to view all submissions)",
-                            value=False,
-                            interactive=True
-                        )
-                        vbench_validate_filter_i2v = gr.Checkbox(
-                                label="Evaluated by VBench Team (Uncheck to view all submissions)",
-                                value=False,
-                                interactive=True
-                            )
-                    checkbox_group_i2v = gr.CheckboxGroup(
-                        choices=I2V_TAB,
-                        value=I2V_TAB,
-                        label="Evaluation Quality Dimension",
-                        interactive=True,
-                    )
-
-            data_component_i2v = gr.components.Dataframe(
-                value=get_baseline_df_i2v, 
-                headers=COLUMN_NAMES_I2V,
-                type="pandas", 
-                datatype=I2V_TITILE_TYPE,
-                interactive=False,
-                visible=True,
-                )
-    
-            checkbox_group_i2v.change(fn=on_filter_model_size_method_change_i2v, inputs=[checkbox_group_i2v, vbench_team_filter_i2v,vbench_validate_filter_i2v], outputs=data_component_i2v)
-            vbench_team_filter_i2v.change(fn=on_filter_model_size_method_change_i2v, inputs=[checkbox_group_i2v, vbench_team_filter_i2v,vbench_validate_filter_i2v], outputs=data_component_i2v)
-            vbench_validate_filter_i2v.change(fn=on_filter_model_size_method_change_i2v, inputs=[checkbox_group_i2v, vbench_team_filter_i2v,vbench_validate_filter_i2v], outputs=data_component_i2v)
         
-        with gr.TabItem("📊 VBench-Long", elem_id="vbench-tab-table", id=4):
-            with gr.Row():
-                with gr.Accordion("INSTRUCTION", open=False):
-                    citation_button = gr.Textbox(
-                        value=LONG_CLAIM_TEXT,
-                        label="",
-                        elem_id="long-ins-button",
-                        lines=2,
-                    )
-    
-            gr.Markdown(
-                TABLE_INTRODUCTION
-            )
-            with gr.Row():
-                with gr.Column(scale=0.2):
-                    choosen_q_long = gr.Button("Select Quality Dimensions")
-                    choosen_s_long = gr.Button("Select Semantic Dimensions")
-                    enable_b_long = gr.Button("Select All")
-                    disable_b_long = gr.Button("Deselect All")
-
-                with gr.Column(scale=0.8):
-                    with gr.Row():
-                        vbench_team_filter_long = gr.Checkbox(
-                            label="Sampled by VBench Team (Uncheck to view all submissions)",
-                            value=False,
-                            interactive=True
-                        )
-                        vbench_validate_filter_long = gr.Checkbox(
-                            label="Evaluated by VBench Team (Uncheck to view all submissions)",
-                            value=False,
-                            interactive=True
-                        )
-                    checkbox_group_long = gr.CheckboxGroup(
-                        choices=TASK_INFO,
-                        value=DEFAULT_INFO,
-                        label="Evaluation Dimension",
-                        interactive=True,
-                    )
-
-            data_component = gr.components.Dataframe(
-                value=get_baseline_df_long, 
-                headers=COLUMN_NAMES,
-                type="pandas", 
-                datatype=DATA_TITILE_TYPE,
-                interactive=False,
-                visible=True,
-                # height=700,
-                )
-    
-            choosen_q_long.click(choose_all_quailty, inputs=None, outputs=[checkbox_group_long]).then(fn=on_filter_model_size_method_change_long, inputs=[ checkbox_group_long, vbench_team_filter_long, vbench_validate_filter_long], outputs=data_component)
-            choosen_s_long.click(choose_all_semantic, inputs=None, outputs=[checkbox_group_long]).then(fn=on_filter_model_size_method_change_long, inputs=[ checkbox_group_long, vbench_team_filter_long, vbench_validate_filter_long], outputs=data_component)
-            enable_b_long.click(enable_all, inputs=None, outputs=[checkbox_group_long]).then(fn=on_filter_model_size_method_change_long, inputs=[ checkbox_group_long, vbench_team_filter_long, vbench_validate_filter_long], outputs=data_component)
-            disable_b_long.click(disable_all, inputs=None, outputs=[checkbox_group_long]).then(fn=on_filter_model_size_method_change_long, inputs=[ checkbox_group_long, vbench_team_filter_long, vbench_validate_filter_long], outputs=data_component)
-            checkbox_group_long.change(fn=on_filter_model_size_method_change_long, inputs=[checkbox_group_long, vbench_team_filter_long,vbench_validate_filter_long], outputs=data_component)
-            vbench_team_filter_long.change(fn=on_filter_model_size_method_change_long, inputs=[checkbox_group_long, vbench_team_filter_long,vbench_validate_filter_long], outputs=data_component)
-            vbench_validate_filter_long.change(fn=on_filter_model_size_method_change_long, inputs=[checkbox_group_long, vbench_team_filter_long,vbench_validate_filter_long], outputs=data_component)
-
         # table info
         with gr.TabItem("📝 About", elem_id="mvbench-tab-table", id=5):
             gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
         
-        # table submission 
-        with gr.TabItem("🚀 [T2V]Submit here! ", elem_id="mvbench-tab-table", id=6):
-            gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
-
-            with gr.Row():
-                gr.Markdown(SUBMIT_INTRODUCTION, elem_classes="markdown-text")
-
-            with gr.Row():
-                gr.Markdown("# ✉️✨ Submit your model evaluation json file here!", elem_classes="markdown-text")
-
-            with gr.Row():
-                gr.Markdown("Here is a required field", elem_classes="markdown-text")
-            with gr.Row():
-                with gr.Column():
-                    model_name_textbox = gr.Textbox(
-                        label="Model name", placeholder="Required field"
-                        )
-                    revision_name_textbox = gr.Textbox(
-                        label="Revision Model Name(Optional)", placeholder="If you need to update the previous results, please fill in this line"
-                    )
-                    access_type = gr.Dropdown(["Open Source", "Ready to Open Source", "API", "Close"], label="Please select the way user can access your model. You can update the content by revision_name, or contact the VBench Team.")
-
-                with gr.Column():
-                    model_link = gr.Textbox(
-                        label="Project Page/Paper Link/Github/HuggingFace Repo", placeholder="Required field. If filling in the wrong information, your results may be removed."
-                    )
-                    team_name = gr.Textbox(
-                        label="Your Team Name(If left blank, it will be user upload)", placeholder="User Upload"
-                    )
-                    contact_email = gr.Textbox(
-                        label="E-Mail(Will not be displayed)", placeholder="Required field"
-                    )
-            with gr.Row():
-                gr.Markdown("The following is optional and will be synced to [GitHub] (https://github.com/Vchitect/VBench/tree/master/sampled_videos#what-are-the-details-of-the-video-generation-models)", elem_classes="markdown-text")
-            with gr.Row():
-                    release_time = gr.Textbox(label="Time of Publish", placeholder="1970-01-01")
-                    model_resolution = gr.Textbox(label="resolution", )#placeholder="Width x Height")
-                    model_fps = gr.Textbox(label="model fps", placeholder="FPS(int)")
-                    model_frame = gr.Textbox(label="model frame count", placeholder="INT")
-                    model_video_length = gr.Textbox(label="model video length", placeholder="float(2.0)")
-                    model_checkpoint = gr.Textbox(label="model checkpoint", placeholder="optional")
-                    model_commit_id = gr.Textbox(label="github commit id", placeholder='main')
-                    model_video_format = gr.Textbox(label="pipeline format", placeholder='mp4')
-            with gr.Column():
-                input_file = gr.components.File(label = "Click to Upload a ZIP File", file_count="single", type='binary')
-                submit_button = gr.Button("Submit Eval")
-                submit_succ_button = gr.Markdown("Submit Success! Please press refresh and return to LeaderBoard!", visible=False)
-                fail_textbox = gr.Markdown('<span style="color:red;">Please ensure that the `Model Name`, `Project Page`, and `Email` are filled in correctly.</span>', elem_classes="markdown-text",visible=False)
-                
-    
-                submission_result = gr.Markdown()
-                submit_button.click(
-                    add_new_eval,
-                    inputs = [
-                        input_file,
-                        model_name_textbox,
-                        revision_name_textbox,
-                        model_link,
-                        team_name,
-                        contact_email,
-                        release_time,
-                        access_type,
-                        model_resolution,
-                        model_fps,
-                        model_frame,
-                        model_video_length,
-                        model_checkpoint,
-                        model_commit_id,
-                        model_video_format
-                    ],
-                    outputs=[submit_button, submit_succ_button, fail_textbox]
-                )
-                
-        with gr.TabItem("🚀 [I2V]Submit here! ", elem_id="mvbench-i2v-tab-table", id=7):
+        with gr.TabItem("🚀 Submit here! ", elem_id="mvbench-i2v-tab-table", id=7):
             gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
 
             with gr.Row():