This paper introduces a computational framework for recovering spectral information from single-shot photos using a specially designed color chart and algorithm, achieving spectral resolution comparable to scientific spectrometers. It eliminates the need for training data or pre-trained models and has potential applications in accessible optical spectroscopy and hyperspectral imaging.
This book covers foundational topics within computer vision, with an image processing and machine learning perspective. It aims to build the reader’s intuition through visualizations and is intended for undergraduate and graduate students, as well as experienced practitioners.
The AI Camera is a portable, low-power device that combines a Raspberry Pi Zero, a 2MP camera module, and a range of sensors, designed for capturing and processing images locally with AI capabilities.
This article explains how to run inference on a YOLOv8 object detection model using Docker and create a REST API to orchestrate the process. It includes code implementation and a detailed README in the author's GitHub repository for running the API via REST with Docker.
The article is about the winners of the OpenCV AI Competition 2023, which was held with the support of Khadas and Seeed Studio. The competition had three categories: Ranked Prize, Finalis
t, and Popular Vote - Finalist.
In the Ranked Prize category, the first place was awarded a Grand Prize Winner Sponsored by KHADAS ($7,472 value), the second place was awarded a 1st Runner-up ($5,472 value), and the thir
d place was awarded a 2nd Runner-up ($4,472 value). The winners in this category were:
* First Place: B-AROL-O - A Four-legged Robot Ensuring Intelligent Sprinkler Automation
* Second Place: OpenCV for Exoplanet Detection
* Third Place: IC4U - Robot Guide Dog for Visually Impaired People