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Update app.py
Browse files
app.py
CHANGED
@@ -129,6 +129,17 @@ def get_baseline_df():
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df = convert_scores_to_percentage(df)
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return df
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def get_all_df(selected_columns):
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submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
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submission_repo.git_pull()
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@@ -178,6 +189,29 @@ def on_filter_model_size_method_change(selected_columns):
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return filter_component#.value
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block = gr.Blocks()
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@@ -186,6 +220,7 @@ with block:
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LEADERBORAD_INTRODUCTION
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)
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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with gr.TabItem("π VBench", elem_id="vbench-tab-table", id=1):
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with gr.Row():
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with gr.Accordion("Citation", open=False):
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@@ -230,6 +265,28 @@ with block:
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disable_b.click(disable_all, inputs=None, outputs=[checkbox_group]).then(fn=on_filter_model_size_method_change, inputs=[ checkbox_group], outputs=data_component)
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checkbox_group.change(fn=on_filter_model_size_method_change, inputs=[ checkbox_group], outputs=data_component)
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# table 2
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with gr.TabItem("π About", elem_id="mvbench-tab-table", id=2):
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gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
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df = convert_scores_to_percentage(df)
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return df
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def get_baseline_df_quality():
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submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
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submission_repo.git_pull()
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df = pd.read_csv(CSV_DIR)
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df = get_final_score(df, checkbox_group.value)
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df = df.sort_values(by="Selected Score", ascending=False)
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present_columns = MODEL_INFO_TAB_QUALITY + checkbox_group_quality.value
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df = df[present_columns]
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df = convert_scores_to_percentage(df)
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return df
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def get_all_df(selected_columns):
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submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
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submission_repo.git_pull()
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)
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return filter_component#.value
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def on_filter_model_size_method_change_quality(selected_columns):
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updated_data = get_baseline_df_quality(selected_columns)
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#print(updated_data)
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# columns:
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selected_columns = [item for item in QUALITY_TAB if item in selected_columns]
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present_columns = MODEL_INFO_TAB_QUALITY + selected_columns
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updated_data = updated_data[present_columns]
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updated_data = updated_data.sort_values(by="Selected Score", ascending=False)
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updated_data = convert_scores_to_percentage(updated_data)
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updated_headers = present_columns
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update_datatype = [DATA_TITILE_TYPE[COLUMN_NAMES.index(x)] for x in updated_headers]
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# print(updated_data,present_columns,update_datatype)
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filter_component = gr.components.Dataframe(
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value=updated_data,
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headers=updated_headers,
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type="pandas",
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datatype=update_datatype,
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interactive=False,
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visible=True,
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)
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return filter_component#.value
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block = gr.Blocks()
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LEADERBORAD_INTRODUCTION
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)
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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# Table 0
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with gr.TabItem("π VBench", elem_id="vbench-tab-table", id=1):
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with gr.Row():
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with gr.Accordion("Citation", open=False):
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disable_b.click(disable_all, inputs=None, outputs=[checkbox_group]).then(fn=on_filter_model_size_method_change, inputs=[ checkbox_group], outputs=data_component)
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checkbox_group.change(fn=on_filter_model_size_method_change, inputs=[ checkbox_group], outputs=data_component)
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with gr.TabItem("Video Quaity", elem_id="vbench-tab-table", id=1):
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with gr.Row():
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with gr.Column(scale=1.0):
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# selection for column part:
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checkbox_group_quality = gr.CheckboxGroup(
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choices=QUALITY_TAB,
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value=QUALITY_TAB,
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label="Evaluation Quality Dimension",
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interactive=True,
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)
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data_component_quality = gr.components.Dataframe(
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value=get_baseline_df_quality,
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headers=COLUMN_NAMES_QUALITY,
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type="pandas",
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datatype=DATA_TITILE_TYPE,
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interactive=False,
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visible=True,
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)
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checkbox_group_quality.change(fn=on_filter_model_size_method_change_quality, inputs=[checkbox_group_quality], outputs=data_component_quality)
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# table 2
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with gr.TabItem("π About", elem_id="mvbench-tab-table", id=2):
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gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
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