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Parallel Processing Using Python for Faster Video Processing

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. How can we speed up video processing? Parallel processing is the answer! If you want to process a number of video files, it might take from minutes to hours, depending on the size of the video, frame …

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How to Annotate Your Images Using the MakeSense Tool

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. In this post, we will cover the details of annotating images using the MakeSense annotation tool. Imagine you just got an exciting project where you have to build a program to detect if a door is open …

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Exploring Data Labeling and the 6 Different Types of Image Annotation

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Data labeling is an essential step in a supervised machine learning task. The same is true for image annotation. Data labeling and image annotations must work together to paint a complete picture. If you show a child …

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Overcome These 6 Problems with Object Detection

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. There are a number of common problems with object detection. For example, can your object detector detect people and horses in the following image? People on horses (Photo by Paul Chambers on Unsplash) What if the same …

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Face Tracking in Python using Xailient Face Detector and Dlib

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Face tracking is detecting a set of faces in frame 1 of a video, establishing a correspondence between the frames, and maintaining a unique ID for each of the faces throughout the video. It is being used …

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Xailient Announces Face Recognition AI for Sony’s Intelligent Vision Sensor IMX500 with Impressive 97.8% Accuracy Up to 3 Meters

SYDNEY, Nov. 29, 2021 /PRNewswire/ — Xailient announced the world’s most power-efficient Face Recognition AI, which runs on the IMX500, the world’s first intelligent vision sensor with edge AI processing capability from Sony Semiconductor Solutions Corporation (“Sony”). Xailient’s Face Recognition enables high-speed edge AI processing with low-power consumption using Sony’s IMX500 – a chip so …

Xailient Announces Face Recognition AI for Sony’s Intelligent Vision Sensor IMX500 with Impressive 97.8% Accuracy Up to 3 Meters Read More +

Face Detection with 7 Lines of Code in Python

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Only a few years ago, if someone asked me to work on a project that required detecting a person’s face using the camera, to be honest, I would have shut down my laptop and run as far …

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Real-time Face Detection on Raspberry Pi

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. A step-by-step guide to implement real-time face detection on a Raspberry Pi running 24 frames per second. In this post, I will guide you through a step-by-step process of implementing real-time face detection on a Raspberry Pi, running …

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