In this comprehensive tutorial, discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model. Learn how to convert object detection datasets into instance segmentation datasets, and use these models to automatically annotate your images.
Most object detection models are trained to identify a narrow predetermined collection of classes. Zero-shot detectors like Grounding DINO want to break this status quo by making it possible to detect new objects without re-training a model.
The article below was contributed by Timothy Malche, an assistant professor in the Department of Computer Applications at Manipal University Jaipur.
Pill Inspection System Overview
This project creates a system
Counting moving objects is one of the most popular use cases in computer vision. It is used, among other things, in traffic analysis and as part of the automation of manufacturing processes. That is why understanding how to do it well is crucial for any CV engineer.
This is a guest post by Kristen Kehrer
, Developer Advocate at CometML [https://www.comet.com/site/]. Since
Manufacturing is an industry that has found many successful use cases and
applications for computer vision. Vision AI helps avoid increases worker safety,
decreases human error, and saves time automating
NVIDIA's TAO Toolkit provides a framework for fine-tuning popular computer vision models using your own data. In this tutorial, we'll be demonstrating how to use Roboflow to curate a high-quality computer vision dataset to use with NVIDIA's TAO Toolkit.
Benefits to Existing Models
Polygons have traditionally been used for training image segmentation models
polygons can also improve the training of object detection models
Polygons have traditionally been used for training image segmentation models, but they can also improve the training of object detection models. Object detection models are typically much faster and more widely supported, so they're still the best choice for solving many problems.
The YOLO (You Only Look Once) family of models
[https://blog.roboflow.com/guide-to-yolo-models/] continues to grow and right
after YOLOv6 was released, YOLOv7 was delivered quickly after