Quickstart

Import a public dataset and get a quality report on it, in about ten minutes.

You’ll build a two-node flow by hand: one node imports a sample of a public dataset from Dataset Ninja, the second profiles it and produces a report. Along the way you’ll meet the three things every flow is made of — nodes, edges and references.

Import from Dataset Ninja Annotation quality

You need an OvalBee account and a workspace where you can edit flows. No GPU, no data of your own and no labeling are needed.

1

Create a flow

On the Home page, click Start from scratch. A blank canvas opens with the AI Chat panel next to it. Close the panel for now — you’ll build this one yourself.

2

Add the import node

Double-click the empty canvas to open the node picker, search for Import from Dataset Ninja and click it, then click the canvas to place it. The node’s sidebar opens on the right.

3

Choose a dataset

In the sidebar, open the Dataset Ninja picker and choose a small dataset from the catalog — for example PCB Component Detection. Set Import size to Sample, so only the smaller published sample is downloaded.

In Destination dataset, type a new name such as Quickstart sample and press Create. You’ve just created an empty dataset that the import will fill.

4

Run the import

Click Run node at the bottom of the sidebar. The node shows its progress on the canvas. Open the History tab in the sidebar to watch the logs live.

When the run completes, the images and their annotations are in the Quickstart sample dataset. You can also find it under Storage in the main sidebar.

5

Add the report node and connect it

Add an Annotation quality node below the import node. Drag from the small handle at the bottom of the import node to the new node to draw an edge.

OvalBee notices that Annotation quality needs a dataset and that the import node produces one, and asks Set variable binding? Click Set binding.

6

Run it and open the report

Select Annotation quality and click Run node. When it completes, click Open report on the node. The report profiles the dataset: statistics about its images, classes and annotations, with charts you can drill into.

What you just built

Look at the flow again with these in mind:

  • Two nodes. Each one is a step that runs on the platform, keeps its own run history and shows its latest result on the canvas.
  • One edge. It means “run Annotation quality after the import succeeds”. From now on, whenever the import runs, the report is rebuilt right after it without you starting it.
  • One reference. The edge doesn’t carry the dataset. The dataset input of Annotation quality references the import node’s output — that’s the binding you accepted. Select the node and look at the input: it shows which node and output it’s bound to, and its current value.

Every flow in OvalBee, from a two-node import to a forty-node labeling operation, is built from these same pieces. Edges and References explain them properly.

Next steps