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Paul
/
Netwave_paul1-project-1
Public
Crop sample ''
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Edit labels for '''
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Timestamps are inclusive - so
{"startMs": 200, "endMs": 202 } includes 200, 201 and 202.
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Alternatively, you can use our
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or import data directly from another project.
CSV and Parquet files will be processed using the active CSV Wizard configuration, which was created using "Left_20230807-191055.txt" (). Download config.
CSV and Parquet files will be processed using the active CSV Wizard configuration, which was created using "Left_20230807-191055.txt" (). Download config.
Bounding boxes: You can upload object detection datasets in
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Image label format
Labeling method
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Select both your images and any label files when uploading to apply the labels.
A label map file could not be detected.
This format requires a label map file, which maps keys to the label they represent.
You can fix these labels later by clicking 'Edit labels' on the data acquisition page.
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Advanced settings
This dataset format uses bounding box labeling, used for object detection.
This dataset format uses one label per sample. You may wish to change your project
labeling method to 'one label per data item' in the project dashboard.
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Data distribution (Training)
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Dataset train / test split ratio
Training data is used to train your model, and testing data is used to test your model's accuracy after training.
We recommend an approximate 80/20 train/test split ratio for your data for every class (or label) in your dataset, although especially large datasets may require less testing data.
Suggested train / test split
80% / 20%
Labels in your dataset
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