Manage Your Data

The Dataset Browser lets you take action at both the dataset and item levels. To get started, select the scope of items you want to work with—either the entire dataset or specific items. Then, click Dataset Actions to access the available options.
Some actions may be unavailable when multiple items are selected.

Right-Click: Right-clicking on an item opens the actions menu. While the menu appears on the item you clicked, the actions apply to all currently selected items. The same set of options is also available under Dataset Actions.

Multi-Select Items:
To select multiple items, hold Ctrl (or Cmd on Mac) and click the items you want to include.

File Actions

You can perform the following action on an item within the Dataset. Please note that actions from the right-click menu cannot apply to multiple selected items simultaneously.

Open Items in a New Tab

It allows you to view images, play audio files, etc. in a new browser tab.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select File Actions > Open File in New Tab. The selected file will be opened in a new browser tab.

Open item in the studio

It allows you to view images, play audio files, etc. in a new browser tab. In the Dataset Browser, identify the item and double-click. The item will be opened in the default annotation studio based on the type of the item, such as image, audio, video, etc. or, you can follow these steps:

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select File Actions > Open File in Studio. The selected file will be opened in the default annotation studio.

Export items as JSON file

1. In the Dataset Browser, select the item you want to export.
2. Click Dataset Actions
3. Select File Actions > Export JSON. The selected dataset or items will be exported as a JSON file in a ZIP file and will contain annotation, if available. For example, a JPG image will be downloaded as a JSON file.

Download Annotations as JSON file

1. In the Dataset Browser, select the item to download annotation.
2. Click Dataset Actions
3. Select File Actions > Download Annotations from the list. The annotations of the selected file will be downloaded as a JSON file.

Rename Items

1. In the Dataset Browser, select the item you want to rename.
2. Click Dataset Actions
3. Select File Actions > Rename.
4. Edit the name, and click Rename. A confirmation message is displayed.

Move Items to a Folder

1. In the Dataset Browser, select the item you want to move.
2. Click Dataset Actions
3. Select File Actions > Move to Folder.
4. Select a folder from the list.
5. Click Move. A confirmation message is displayed.

Classify Items

1. In the Dataset Browser, select the item you want to classify.
2. Click Dataset Actions
3. Select File Actions > Classification from the list. Learn more about the classification.

Clone Items

1. In the Dataset Browser, select the item you want to clone.
2. Click Dataset Actions
3. Select File Actions > Clone. Learn more about the cloning process.

Download Files

1. In the Dataset Browser, select the item(s) you want to export.
2. Click Dataset Actions
3. Select File Actions > Download Files. The selected item will be downloaded. For example, JPG image will be downloaded as a JPG file.

Delete Annotations from Items

1. In the Dataset Browser, select the item you want to delete annotations.
2. Click Dataset Actions
3. Select File Actions > Delete Annotations. A confirmation message is displayed.

Delete Dataset Items

1. In the Dataset Browser, select the item you want to delete.
2. Click Dataset Actions
3. Select File Actions > Delete Items.
4. Click Yes. A confirmation message is displayed.

Open With

The Open With option allows you to open items in the respective labeling studios.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions -> Open With.
3. Select the Annotation Studio. The type of the annotation studio will display based on the type of the item, such as image, audio, video, etc.

Labeling tasks

Create a Task

1. In the Dataset Browser, Click Dataset Actions
2. Select Labeling Tasks -> Create a New Task from the list. Learn more

Add a Dataset to an Existing Task

1. In the Dataset Browser, click Dataset Actions
2. Select Labeling Tasks -> Add to an Existing Task from the list.

Models

Predictions with a Model

You can use the dataset items to generate predictions by using a trained, pre-trained, and deployed model.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models > Predict.
4. Search and select a trained and deployed model from the list.
5. Click Predict. A confirmation message is displayed.

Predictions by a Trained Model

You can use only trained and deployed models for generating predictions. To deploy a trained model, perform the following instructions:

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models > Predict.
4. Identify the trained model, and click Deploy. The Model Version Deployment page is displayed.
5. In the Deployment and Service Fields tabs, make changes in the available fields as needed.
6. Click Deploy. A confirmation message is displayed.

Assign items to test subsets

You can assign the selected items to model's test datasets. When you assign, a tag (Test) will be added to the item details.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models -> Assign to Subset.
4. Select the Test. The Test Dataset is used to evaluate the performance of a trained model on new, unseen data.

Assign Items to Train Subsets

You can assign the selected items to model's train datasets. When you assign, a tag (Train) will be added to the item details.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models -> Assign to Subset.
4. Select the Train. The Train Dataset is used to train the machine learning model, helping it learn patterns and make predictions.

Assign Items to Validation Subsets

You can assign the selected items to model's Validation datasets. When you assign, a tag (Validation) will be added to the item details.

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models -> Assign to Subset.
4. Select the Validation. The Validation Dataset is used to fine-tune the model and optimize its hyperparameters, helping prevent overfitting.

Embeddings from Items

1. In the Dataset Browser, select the items you want to extract embeddings.
2. Click Dataset Actions and select the Models -> Extract Embeddings option from the list. An Extract Embeddings pop-up is displayed.

3. Select a Model from the Deployed section, or click on the Marketplace to install a new model. If there are no models available, click Install Model.
   1. Once installed a model, click Deploy
4. Click Embed to initiate the embeddings' extraction. Use the Notifications bell icon to view status.

Split Items into ML Subsets

Refer to the Split Into Subsets article.

Remove Items from Subsets

1. In the Dataset Browser, select the item.
2. Click Dataset Actions
3. Select Models.
4. Select the following options as per requirement. A confirmation message will be displayed, and the respective tag will be deleted from the item details.
   1. Remove from Test Set.
   2. Remove from Train Set.
   3. Remove from Validation Set.

Deployment slot

The Dataset browser incorporates significant automation capabilities, enabling you to export dataset items in industry-standard formats through the following functions. Any function available within this application can be applied to selected items or an active query.

In addition to the Dataloop format, annotations can be exported in industry-standard formats. These are facilitated as functions deployed to the UI Slot of the Dataset-browser.

To learn more about the converters, their input, and output structures, visit their Git repo.

• COCO Converter: This tool is used to convert data annotations from other formats into the COCO (Common Objects in Context) format or vice versa. COCO is a popular dataset format for object detection, segmentation, and image captioning tasks.
• YOLO Converter: YOLO (You Only Look Once) is a popular object detection algorithm. A YOLO Converter is used to convert annotations between YOLO format and other annotation formats, making it easier to work with YOLO-based models and datasets.
• VOC Converter: VOC (Visual Object Classes) is another dataset format commonly used in computer vision tasks. A VOC Converter allows you to convert annotations between VOC format and other formats, facilitating compatibility with different tools and models.

Export datasets in COCO/YOLO/VOC formats

1. In the Dataset Browser, select the item(s) in the Dataset Browser.
2. Click Dataset Actions
3. Select Deployment Slot and select one of the following format:
   1. COCO Converter.
   2. YOLO Converter.
   3. VOC Converter.
4. A message is displayed as the execution of function <global-converter> was created successfully, please check activity bell. A ZIP file will be created and downloaded.

Collections

The Collections feature in Dataloop's Data Browser helps streamline data management by allowing you to tag or group specific sets of items based on task needs (e.g., annotation, review, training).
Selecting this option allows you to add selected items to a collection folder.

Similarity

The Similarity feature in Dataloop enables you to identify items that are similar to a selected item. This helps with data exploration, cleaning, and optimizing ML subset splits. To use this feature, ensure that the selected item has an available feature vector. After selecting the Similarity -> Find similar items, you can view all associated feature set names and the model name that generated the item's vector.

Find Similar Items

1. In the Dataset Browser, select the item to download annotation.
2. Click Dataset Actions

3. Select Similarity -> Find similar items
4. Click on the Feature Set name. The Clustering tab is displayed with similar items are selected.

Run Items with Applications

A list of active applications is displayed, and select one of the applications to run the chosen item(s).

1. In the Dataset Browser, select the item.

2. Click Dataset Actions

3. Select the Run with FaaS to select a function to execute with the selected items.

   

4. You can:

   1. Search functions by function name, project name, and service name.

   2. Filter functions by public functions, project functions and all functions in the user’s projects.

      

5. Select a function from the list.

6. Click Execute. A confirmation message will be displayed.

Run Items with Pipelines

A list of active pipelines containing input items is displayed. Select one of the pipelines to run the chosen item(s). Once selected and executed, the pipeline will be triggered starting from its start node.

1. In the Dataset Browser, select the item.

2. Click Dataset Actions

3. Select the Run with Pipeline. It allows you to execute the selected items in the selected pipeline.

   

4. Search and select a pipeline from the list.

5. Click Execute. A confirmation message will be displayed.

Learn more about Pipelines.

To view more actions available on the dataset actions, refer to the Manage Datasets article.