Imagine you have multiple warehouses in different places where you don't have time to monitor everything at a time, and you can't afford a lot of computes due to their cost and unreliability. However, ...
Object Detection on Edge Device: Deploying YOLOv8 on Luxonis OAK-D-Lite – Pothole Datset
Performing Object Detection on edge device is an exciting area for tech enthusiasts where we can implement powerful computer vision applications in compact, efficient packages. Here we show one ...
TensorFlow Model Optimization Toolkit – A Deep Dive
In the previous posts of the TFLite series, we introduced TFLite and the process of creating a model. In this post, we will take a deeper dive into the TensorFlow Model Optimization. We will explore ...
TensorFlow Lite Model Maker: Create Models for On-Device Machine Learning
In this article, we will learn how to create a TensorFlow Lite model using the TF Lite Model Maker Library. We will fine-tune a pre-trained image classification model on the custom dataset, further ...
TensorFlow Lite: TFLite Model Optimization for On-Device Machine Learning
The recent trend in developing larger and larger Deep Learning models for a slight increase in accuracy raises concerns about their computational efficiency and wide scaled usability. We can not use ...
Object Detection With Depth Measurement Using Pre-trained Models With OAK-D
This is the third blog post in the Oak series. If you haven't checked out the previous posts on OAK, check them below. In this post, we are going to look at how we can run an existing pre-trained ...
