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Classes

RawDataApi


METHODS

batch_add_metadata

Add metadata (multiple samples) Add specific metadata for multiple samples.

batch_back_to_labeling

Put samples back into the object detection labeling queue Batch operation to put multiple samples back into the object detection labeling queue. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_clear_metadata

Clear all metadata (multiple samples) Clears all metadata for multiple samples.

batch_clear_metadata_by_key

Clear metadata by key (multiple samples) Clears a specific metadata field (by key) for multiple samples.

batch_delete

Remove multiple samples Deletes samples. Note that this does not delete the data from cold storage. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_disable

Disable multiple samples Disables samples, ensuring that they are excluded from the dataset. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_edit_bounding_boxes

Edit bounding boxes for multiple samples Relabels (or removes) bounding boxes for multiple samples. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_edit_labels

Edit labels for multiple samples Sets the label (also known as class) of multiple samples. If you want to relabel bounding boxes, use “batchEditBoundingBoxes” instead. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_enable

Enable multiple samples Enables samples, ensuring that they are not excluded from the dataset. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

batch_move

Move multiple samples Move multiple samples to another category (e.g. from test to training). Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.

classify_using_autolabel

Auto-label an image Classify an image using another neural network.

clear_all_object_detection_labels

Clear all object detection labels Clears all object detection labels for this dataset, and places all images back in the labeling queue.

clear_data_explorer

Clear data explorer Remove the current data explorer state

count_samples

Count samples Count all raw data by category.

crop_sample

Crop sample Crop a sample to within a new range.

delete_all_samples

Remove all samples Deletes all samples for this project over all categories. This also invalidates all DSP and learn blocks. Note that this does not delete the data from cold storage.

delete_all_samples_by_category

Remove all samples by category Deletes all samples for this project over a single category. Note that this does not delete the data from cold storage.

delete_sample

Remove sample Deletes the sample. Note that this does not delete the data from cold storage.

disable_sample

Disable sample Disable a sample, ensuring that it is excluded from the dataset.

edit_label

Edit label Sets the label (also known as class) of the sample. Use the same label for similar types of data, as they are used during training.

enable_sample

Enable sample Enable a sample, ensuring that it is not excluded from the dataset.

find_segments_in_sample

Find segments Find start and end times for all non-noise events in a sample

get_ai_actions_proposed_changes

Get AI Actions proposed changes Get proposed changes from an AI Actions job.

get_all_imported_from

List data with “imported from” metadata key Lists all data with an ‘imported from’ metadata key. Used to check in a data source which items are already in a project.

get_data_explorer_features

Get data explorer features t-SNE2 output of the raw dataset

get_data_explorer_predictions

Get data explorer predictions Predictions for every data explorer point (only available when using current impulse to populate data explorer)

get_data_explorer_settings

Get data explorer settings Get data explorer configuration, like the type of data, and the input / dsp block to use.

get_dataset_ratio

Get dataset ratio Retrieve number of samples in train and test set.

get_diversity_data

Get diversity metrics data Obtain metrics that describe the similarity and diversity of a dataset. To calculate these metrics, use the calculateDataQualityMetrics endpoint.

get_label_noise_data

Get label noise data Obtain metrics that describe potential label noise issues in the dataset. To calculate these metrics, use the calculateDataQualityMetrics endpoint.

get_object_detection_label_queue

Object detection label queue Get all unlabeled items from the object detection queue.

get_object_detection_label_queue_count

Object detection label queue count Get count for unlabeled items from the object detection queue.

get_sample

Get sample Get a sample.

get_sample_as_audio

Get WAV file Get a sample as a WAV file. This only applies to samples with an audio axis.

get_sample_as_image

Get image file Get a sample as an image file. This only applies to samples with RGBA data.

get_sample_as_raw

Download file Download a sample in it’s original format as uploaded to the ingestion service.

get_sample_as_video

Get video file Get a sample as an video file. This only applies to samples with video data.

get_sample_metadata

Get project sample metadata Get metadata for all samples in a project.

get_sample_metadata_filter_options

Get project sample metadata filter options Get a list of unique key value pairs across all samples in a project that can be applied as filters to the /api/{projectId}/raw-data endpoint

get_sample_slice

Get sample slice Get a slice of a sample.

get_uncropped_downsampled_sample

Get the original downsampled data Get the original, uncropped, downsampled data.

has_data_explorer_features

Check data explorer features t-SNE2 output of the raw dataset

has_diversity_data

Check if data diversity metrics exist Determine if data diversity metrics have been calculated. To calculate these metrics, use the calculateDataQualityMetrics endpoint.

has_label_noise_data

Check if label noise metrics exist Determine if label noise metrics have been calculated. To calculate these metrics, use the calculateDataQualityMetrics endpoint.

list_samples

List samples Retrieve all raw data by category.

move_sample

Move sample Move a sample to another category (e.g. from test to training).

move_to_labeling_queue

Move sample to labeling queue Clears the bounding box labels and moves item back to labeling queue

rebalance_dataset

Rebalance dataset This API is deprecated, use rebalanceDatasetV2 instead (/v1/api/{projectId}/v2/rebalance). Rebalances the dataset over training / testing categories. This resets the category for all data and splits it 80%/20% between training and testing. This is a deterministic process based on the hash of the name of the data.

rebalance_dataset_v2

Rebalance dataset Rebalances the dataset over training / testing categories. This resets the category for all data and splits it 80%/20% between training and testing. This is a deterministic process based on the hash of the name of the data. Returns immediately on small datasets, or starts a job on larger datasets. To get the dataset ratio (as returned by the v1 endpoint), use getDatasetRatio.

rename_sample

Rename sample Sets the file name of the sample. This name does not need to be unique, but it’s highly recommended to do so.

retry_processing

Retry processing If a sample failed processing, retry the processing operation.

segment_sample

Segment sample Slice a sample into multiple segments. The original file will be marked as deleted, but you can crop any created segment to retrieve the original file.

set_data_explorer_settings

Set data explorer settings Set data explorer configuration, like the type of data, and the input / dsp block to use.

set_sample_bounding_boxes

Set bounding boxes Set the bounding boxes for a sample

set_sample_metadata

Set sample metadata Adds or updates the metadata associated to a sample.

set_sample_proposed_changes

Propose changes Queue up changes to an object as part of the AI Actions flow. This overwrites any previous proposed changes.

set_sample_structured_labels

Update structured labels Set structured labels for a sample. If a sample has structured labels the label column is ignored, and the sample is allowed to have multiple labels. An array of { startIndex, endIndex, label } needs to be passed in with labels for the complete sample (see valuesCount to get the upper bound). endIndex is inclusive. If you pass in an incorrect array (e.g. missing values) you’ll get an error back.

set_sample_video_dimensions

Set sample video dimensions Update the video dimensions for a sample. This is only available for video files that do not have dimensions set yet.

split_sample_in_frames

Split sample into frames Split a video sample into individual frames. Depending on the length of the video sample this will either execute immediately or return the ID of a job that will perform this action.

store_segment_length

Store the last segment length When segmenting a sample into smaller segments, store the segment length to ensure uniform segment lengths.

track_objects

Track objects Track objects between two samples. Source sample should have bounding boxes set.