A dataset of images, used for computer vision tasks, could be the key to success or failure. A clean dataset could lead the way to a great algorithm and model
A visual dataset used for computer vision tasks, could be the key to success or failure. So how do you make sure your algorithm and model are based on strong foundations?
Data Explorer allows you to search the dataset for images that are similar to a certain image. Searching is performed based on the feature vector of each image with no metadata required.
In this blog, we will see how to automatically select a subset of images for training.
Data Explorer manipulates videos, modifies frame rate for faster processing, splits them into scenes and allows for further curation and exploration.
We see how to perform an image based search or a patch based search in a video, and increase the chances of finding results in different scenes.
Data Explorer is a platform that was built to allow us focus on the data, curate it, clean it and make sure we start the development cycles with a great foundation.
Use Data Explorer in the Kaggle RSNA Mammography competition or EDA and coreset selection
CVPR 2022 Recap CVPR Recap: Akridata Key Takeaways We are all jazzed up! We attended CVPR in New Orleans at the end of June and had a great time seeing everyone there, talking computer vision, visual data, and displaying Akridata Data Explorer. Couldn’t make the event? No problem! Below we’ll dive into our top takeaways, […]