Yolo for Android and iOS - Mobile Deep Learning Object Detection in Realtime written in Kotlin and Swift

A swift project exploring a methodology for face and object auto-cropping using CoreML, GrabCut and YOLO networks.

Automated Drowning Detection: A repository showcasing a deep learning-based solution using YOLO v8 architecture for swift and accurate identification of drowning instances in aquatic environments. Enhanced accuracy through meticulous fine-tuning and integrated methodologies. Empowering drowning incident response systems for improved efficiency.

SwiftUI app that uses the YOLOv8s model to detect objects in the live camera feed.

High-performance Swift library for ML image preprocessing & postprocessing. One-line APIs for TFLite, CoreML, PyTorch/ExecuTorch. Supports classification, detection (YOLO), segmentation (DeepLabV3), quantization, augmentation, and visualization.

Exact Implementation of YOLOv4 in Swift for TensorFlow

YOLO v3 on OpenImages dataset in CoreML with Vision implemented for iPhone iOS in Swift

This project combining ResNet for face identification into a weapon detecting system using YOLO. The algorithm analyses live surveillance footage using ResNet for identifying criminals and YOLO for spotting potential threats like weapons, aiding proactive crime prevention by swiftly alerting law enforcement.

http://larsacus.github.io/swift-yolo/ I hope you thought long and hard before using swift's force-unwrapped optionals.

Using Swift, Yolo module and openCV.

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An IOS app that detects objects using YOLOV3 Algorithm with CoreML

forked from yolov5-swift

A Swift implementation of mAP computation for Yolo-style detections

yolo,esp32s3,小智ai

Real-time number plate detection via YOLO V8: A swift, accurate system using advanced computer vision. Detects plates in live video feeds, aiding traffic control, law enforcement. Fast, precise, and pivotal for security, traffic management.

Experience the power of real-time sign language detection using YOLO, a cutting-edge object detection framework. This project combines computer vision and accessibility to enable instant recognition of sign language gestures from live video streams. Using YOLOv3 or YOLOv4 the model swiftly identifies hand gestures directly from video frames

This Google Colab notebook provides a complete training pipeline for deploying a Swift-YOLO object detection model optimized for the Grove Vision AI V2 module. Custom models can be downloaded to https://sensecraft.seeed.cc/ai/model.

YOLOv5 와 SwiftUI, PencilKIt 을 이용한 필기 인식 기반 악보 작성 앱

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create an application called yoloopoor on iOS using swift language (based on material from udemy learn to be an iOS developer)

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Creating a productive app called yoloodaily on iOS using swift language to increase productivity in daily activities

YOLOv26实现Maruti Suzuki Swift车型识别与分类

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Face Tracking Demo with Swift and YOLO on XIAO and Grove Vision Board v2

Real-Time Helmet Detection: Utilizing YOLO v8 for swift and precise identification of helmets, enhancing workplace safety in industrial settings

Real-time weapon detection with YOLO swiftly identifies firearms in live video. Powered by efficient object detection, it ensures rapid response for enhanced security.

Leveraging YOLO and Intel RealSense LiDAR 515 to compute precise volumes swiftly. Ideal for robotics, logistics, and industrial applications, ensuring efficient spatial analysis and object measurement