9 ???? Object Detection Datasets

Author(s): Akula Hemanth Kumar

Originally published on Towards AI.

Starter code Available using Monk Libraries

In this article, I am going to share a few datasets for Object Detection. Starter code is provided in Github and you can directly run them in Colab.

P.S: Description of dataset is taken directly from the websites.

1. Traffic Sign Recognition U+1F6A6U+1F6B3

The LISA Traffic Sign Dataset is a set of videos and annotated frames containing US traffic signs.

• Monk Starter code: Github

2. Exclusively-Dark-Image-Dataset U+1F9B8‍U+2642️

It is the largest collection of low-light images taken in very low-light environments to twilight (i.e 10 different conditions) to-date with image class and object-level annotations.

• Monk Starter code: Github

3.WGISD U+1F347

It provides images and annotations to study object detection and instance segmentation for image-based monitoring and field robotics in viticulture.

• Monk Starter code: Github

4.TACO U+1F37E

TACO is an open image dataset of waste in the wild. It contains photos of litter taken under diverse environments. Annotations are provided in the COCO format.

• Monk Starter code: Github

5.Open Images Dataset

Open Image is a dataset of ~9M images annotated with image-level labels, object bounding boxes, object segmentation masks, visual relationships, and localized narratives. It contains a total of 16M bounding boxes for 600 object classes on 1.9M images, making it the largest existing dataset with object location annotations.

• Monk Starter code for Billboard: Github
• Monk Starter code for Football: Github

6.CAMEL Dataset U+1F42B

It provides visual-infrared object detection and tracking.

• Monk Starter code: Github

7.Playing Card

It provides playing cards object detection.

• Monk Starter code: Github

8.DeepFashion2 U+1F455

DeepFashion2 is a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers.

• Monk Starter code: Github

9.WIDER Pedestrian Detection

The main goal of the WIDER Person Challenge is to address the problem of detecting pedestrians and cyclists in unconstrained environments.

• Monk Starter code: Github

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Published via Towards AI