Fingerspelling embedding + ClearML
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@@ -8,7 +8,6 @@ dataset = "data/processed/spoter.csv"
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# read the dataset
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df = pd.read_csv(dataset)
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df = map_blazepose_df(df)
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with open("data/sign_to_prediction_index_map.json", "r") as f:
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sign_to_prediction_index_max = json.load(f)
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@@ -17,6 +16,9 @@ with open("data/sign_to_prediction_index_map.json", "r") as f:
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# filter df to make sure each sign has at least 4 samples
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df = df[df["sign"].map(df["sign"].value_counts()) > 4]
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# print number of unique signs
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print("Number of unique signs: ", len(df["sign"].unique()))
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# use the path column to split the dataset
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paths = df["path"].unique()
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