In this article, we have presented UCF101 which is one of the most testing dataset for activity acknowledgement contrasted with the current ones. It incorporates 101 activity classes and over 13k clips
UCF-101 dataset has 101 actions and 13320 clips of human actions, collected from youtube were first introduced in 2012 by researchers: Khurram Soomro, Amir Roshan Zamir and Mubarak Shah of Center for Research in Computer Vision, Orlando, FL 32816, USA. The clips in the action class are divided into 25 groups. Each group contains 4-7 clips. Clips in each group share some common features like background or actor.
UCF Sports, UCF11, UCF50 and UCF101 are the datasets arranged by UCF in sequential order, each one incorporates its forerunner. UCF-101 is the largest among them with 101 classes. This dataset gives the biggest variety as far as activities and with the presence of huge varieties in camera movement, object appearance and posture, object scale, perspective, jumbled foundation, light conditions.
Here, we will discuss the dataset and see how to load the dataset using TensorFlow and PyTorch. Further, we will implement the UCF-101 dataset in TensorFlow.
Moment in Time is one of the biggest human-commented video datasets catching visual short occasions created by people, creatures and nature.
Sentiment analysis is a technique in natural language processing that deals with the order of assessments communicated in a bit of text.
TensorFlow is an end-to-end open-source machine learning platform capable of performing a range of tasks. It provides an ease of use for beginners and researchers alike and can be used to work on different applications like, but not limited to, computer vision, natural language processing, and reinforcement learning.
Facebook AI open-sourced a new high-speed library for training PyTorch models with differential privacy (DP) known as Opacus.
Using pre-existing computer vision models for object detection. In my last blog, I discussed some basics concepts of computer vision and how to create a facial recognition filter using OpenCV. But what if you want to detect in an image something other than faces?