Here is an example of how you can run 3 object detection algorithms with the same 8 lines of code in a few seconds. We use face detection from Kornia, YOLOv5 object detection from Ultralytics and Detectron2 keypoints from Meta AI. More info on our Github repo : https://github.com/Ikomia-dev/IkomiaApi How Read more…
While it’s quite simple to launch object detection from pre-trained models, things may become harder when training your custom object detection model. This post describes how this task is efficiently tackled in few clicks with Ikomia platform. Automatic grapes detection Our use case today aims at detecting grapes in the Read more…
Let us introduce you to the Batch Processing mode of Ikomia platform. This tutorial is the logical continuation of how to use Ikomia STUDIO. Therefore, we assume that you are aware of the workflow key features before reading these lines. – 5 min read – An extension to iterate over Read more…
– 10 min read – What is Ikomia STUDIO ? Testing and evaluating Computer Vision algorithms quickly and easily is one of the main goals of the Ikomia platform. That is why we provide different levels of use, from nocode Computer Vision with the STUDIO to low-code with the Python Read more…
Ikomia Use Case: Facial Landmark Detection using OpenCV – 5 min read – Facial Landmark Detection is an important task in many applications such as emotion recognition in marketing, drowsiness detection in automotive or automatic facial makeup. Today, we will explain how to detect facial landmarks in your images or Read more…