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YAML Metadata Warning:The task_categories "time-series-classification" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
ASL Keypoint Dataset - 84 Classes
This dataset contains preprocessed MediaPipe Holistic keypoint sequences for isolated sign language classification.
Dataset Version
This version keeps only classes with at least 50 training samples. In your current filtered version, this produced 84 classes.
Files
train_features_50plus.npytrain_labels_50plus.npyval_features_50plus.npyval_labels_50plus.npyid_to_label_50plus.jsonlabel_to_id_50plus.jsonold_to_new_label_ids_50plus.jsonnew_to_old_label_ids_50plus.jsonclass_counts_after_filtering_50plus.csvfilter_metadata_50plus.json
Important Note
The label IDs have been remapped after filtering. During inference, use id_to_label_50plus.json to convert model output IDs back to sign labels.
Metadata
{
"hf_repo_id": "SharoonArshad/training_model23",
"repo_type": "dataset",
"min_samples": 50,
"local_repo_path": "/kaggle/working/training_model23_raw",
"original_train_samples": 64284,
"filtered_train_samples": 6770,
"original_val_samples": 8188,
"filtered_val_samples": 862,
"original_num_classes": 2310,
"filtered_num_classes": 84,
"train_features_shape": [
6770,
50,
204
],
"val_features_shape": [
862,
50,
204
]
}
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