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| from data.model_handler import ModelHandler | |
| def make_clickable_model(model_name, link=None): | |
| if link is None: | |
| desanitized_model_name = model_name.replace("_", "/") | |
| desanitized_model_name = desanitized_model_name.replace("-thisisapoint-", ".") | |
| if "/captioning" in desanitized_model_name: | |
| desanitized_model_name = desanitized_model_name.replace("/captioning", "") | |
| if "/ocr" in desanitized_model_name: | |
| desanitized_model_name = desanitized_model_name.replace("/ocr", "") | |
| link = "https://huggingface.co/" + desanitized_model_name | |
| return f'<a target="_blank" style="text-decoration: underline" href="{link}">{desanitized_model_name}</a>' | |
| def add_rank_and_format(df, benchmark_version=1): | |
| df = df.reset_index() | |
| df = df.rename(columns={"index": "Model"}) | |
| df = ModelHandler.add_rank(df, benchmark_version) | |
| df["Model"] = df["Model"].apply(make_clickable_model) | |
| # df = remove_duplicates(df) | |
| return df | |
| def remove_duplicates(df): | |
| """Remove duplicate models based on their name (after the last '/' if present).""" | |
| df["model_name"] = df["Model"].str.replace("_", "/") | |
| df = df.sort_values("Rank").drop_duplicates(subset=["model_name"], keep="first") | |
| df = df.drop("model_name", axis=1) | |
| return df | |
| def get_refresh_function(model_handler, benchmark_version): | |
| def _refresh(metric): | |
| model_handler.get_vidore_data(metric) | |
| data_task_category = model_handler.compute_averages(metric, benchmark_version) | |
| df = add_rank_and_format(data_task_category, benchmark_version) | |
| return df | |
| return _refresh | |
| def filter_models(data, search_term): | |
| if search_term: | |
| data = data[data["Model"].str.contains(search_term, case=False, na=False)] | |
| return data | |