Accelerate Building Custom Computer Vision Datasets With This Script💨

A script that downloads images and prepares them for annotation using the Flickr API and makesense.ai

Have you ever wanted to build a model to detect raccoons but didn’t find any open-source annotated images to train it? I was in this situation.

And quite frankly, every person I know who is working in computer vision was once in this situation: building a custom computer vision dataset.

If you’re a bit familiar with the computer vision ecosystem, you’ve probably heard about the common huge image databases such as ImageNet or COCO.

These are large datasets of carefully annotated images that have been open-sourced by research labs and tech companies. They are also considered standard benchmark datasets for evaluating state-of-the-art models.

Some ImageNet and COCO thumbnails

Some ImageNet and COCO thumbnails

They contain millions of images and hundreds of classes along with rich metadata of tags, bounding boxes, or segmentation masks.

So, there’s a high chance that whenever you want to build an image classifier or an object detector, the thing you’re specifically looking for is already there.

But what if you’re looking for objects that are not in these databases?

Short answer…