YOLOv5 is an application that brings the power of advanced Artificial Intelligence (AI) to your iOS device camera. It utilizes cutting-edge technology to detect, classify, and locate up to 80 different types of common objects in real-time.
This impressive software has been trained on the COCO 2017 dataset using PyTorch and then exported to Apple CoreML through their open-source GitHub repository. This transparent approach ensures the credibility and reliability of the AI model.
With A14 iOS devices, YOLOv5 delivers impressive performance, offering over 30 frames per second at a default inference size of 192 x 320. However, it is important to note that older devices may experience slightly slower performance.
An important advantage of YOLOv5 is that all processing is done on-device. This means that images are not transmitted off-device, ensuring privacy and security.
For more information and in-depth details about YOLOv5, please visit their official GitHub repository at: https://github.com/ultralytics/yolov5
Overview
iDetection is a Freeware software in the category Audio & Multimedia developed by Ultralytics LLC.
The latest version of iDetection is 8.0.0, released on 02/11/2024. It was initially added to our database on 02/11/2024.
iDetection runs on the following operating systems: iOS.
Users of iDetection gave it a rating of 4 out of 5 stars.
Pros
- Highly accurate object detection capabilities.
- Real-time processing speeds suitable for dynamic environments.
- User-friendly interface that simplifies deployment.
- Pre-trained models available to save time and computational resources.
- Flexible API that integrates easily with various applications and platforms.
- Strong community support and extensive documentation available.
- Regular updates with new features and optimizations.
Cons
- Requires a good understanding of machine learning concepts for optimal use.
- Can be resource-heavy, necessitating robust hardware for best performance.
- Dependence on internet connectivity for cloud-based features.
- Less effective in detecting small objects compared to larger ones.
- Potentially high costs associated with heavy usage or enterprise-level features.
Screenshots (Click to view larger)
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