Update app.py
Browse files
app.py
CHANGED
@@ -1,12 +1,35 @@
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import gradio as gr
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import pandas as pd
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df = pd.
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headline = """#
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Please include in your email 1) a name for your model, 2) your team name (including your affiliation), and optionally, 3) a github repo or paper link.
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"""
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demo = gr.Blocks()
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with demo:
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@@ -16,7 +39,8 @@ with demo:
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with gr.Column():
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leaderboard_df = gr.components.DataFrame(
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value=df,
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datatype=["markdown", "number", "number", "number"]
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)
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demo.launch()
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# import gradio as gr
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# import pandas as pd
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# df = pd.read_csv('FuseReviews_leaderboard.csv')
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# headline = """# FuseReviews Leaderboard
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# When submitting your results to the leaderboard, please make sure it is in a csv file with a single column "predictions". Make sure the predictions align to the testset order. Please send your predictions to [this mail](mailto:lovodkin93@gmail.com).
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# Please include in your email 1) a name for your model, 2) your team name (including your affiliation), and optionally, 3) a github repo or paper link.
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# """
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# demo = gr.Blocks()
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# with demo:
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# with gr.Row():
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# gr.Markdown(headline)
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# with gr.Column():
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# leaderboard_df = gr.components.DataFrame(
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# value=df,
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# datatype=["markdown", "number", "number", "number"]
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# )
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# demo.launch()
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import gradio as gr
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import pandas as pd
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# df = pd.read_table("visit_bench_leaderboard.tsv")
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df = pd.read_table('visitbench_leaderboard_Single~Image_Nov072023.tsv')
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headline = """# VisIT-Bench Leaderboard
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To submit your results to the leaderboard, you can run our auto-evaluation code, following the instructions [here](https://github.com/Hritikbansal/visit_bench_sandbox). Once you are happy with the results, you can send to [this mail](mailto:yonatanbitton1@gmail.com).
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Please include in your email 1) a name for your model, 2) your team name (including your affiliation), and optionally, 3) a github repo or paper link. Please also attach your predictions: you can add a "predictions" column to [this csv](https://huggingface.co/datasets/mlfoundations/VisIT-Bench/raw/main/test/metadata.csv).
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"""
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demo = gr.Blocks()
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with demo:
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with gr.Column():
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leaderboard_df = gr.components.DataFrame(
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value=df,
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datatype=["markdown", "markdown", "number", "number", "number"]
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)
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demo.launch()
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