YoloV8

In-Depth Guide to YOLOv8 TensorRT C++ Deployment: From XMake Build to Inference Pipeline

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In-Depth Guide to YOLOv8 TensorRT C++ Deployment: From XMake Build to Inference Pipeline

This project has been uploaded to GitHub https://github.com/Bayesianovich/yolov8-fire-smoke-detection, feel free to star ⭐ ⭐ Project Overview This project is a high-performance fire and smoke detection system based on YOLOv8 and TensorRT, implemented in C++, with the following features: Real-time Detection Performance: Achieves high-performance inference using TensorRT GPU acceleration Intelligent Dual Condition Trigger: Alarm is triggered … Read more

RK3588 C++ Visual Deployment Course Introduction

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RK3588 C++ Visual Deployment Course Introduction

Reply to the public account: course, to obtain resources. RK3588 C++ Visual Deployment Course Introduction {“type”:”load_by_key”,”key”:”banner_image_0″,”image_type”:”search”} 1. Course Details This course focuses on in-depth explanations of visual deployment using C++ on the RK3588 platform. As a leading domestic chip, the RK3588 features a quad-core Cortex-A76 and a quad-core Cortex-A55 processor architecture, combined with an integrated … Read more

PCB Defect Detection Based on Deep Learning YOLOv8 and YOLOv5

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PCB Defect Detection Based on Deep Learning YOLOv8 and YOLOv5

Abstract Printed Circuit Boards (PCBs) play a crucial role in electronic devices, and defect detection during their manufacturing process is a key step in ensuring product quality. In recent years, deep learning technologies have made significant progress in object detection tasks, particularly with the YOLO (You Only Look Once) series of algorithms, which excel in … Read more

Deploying YOLOv8 on Wildfire RK3588

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Deploying YOLOv8 on Wildfire RK3588

Description Deploying YOLOv8 on Wildfire RK3588, we will use yolov8s.pt (downloaded from the YOLOv8 official website) as an example. 1. pt->onnx Do not use the official YOLOv8 code; instead, use the Rockchip YOLOv8 code available at the following address: https://github.com/airockchip/ultralytics_yolov8 After downloading the code, execute the model conversion with the following code: from ultralytics import … Read more

Deploying YOLOv8 on Wildfire RK3588

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Deploying YOLOv8 on Wildfire RK3588

Description Deploying YOLOv8 on Wildfire RK3588, we use yolov8s.pt (downloaded from the YOLOv8 official website) as an example. 1. pt->onnx Do not use the official YOLOv8 code; instead, use the Rockchip YOLOv8 code, available at https://github.com/airockchip/ultralytics_yolov8 After downloading the code, execute the model conversion with the following code: from ultralytics import YOLO model = YOLO('yolov8s.pt') … Read more

Using the RK3588 Chip NPU: YOLOv8-Pose Example for Image Detection Deployment on Android System and In-Depth Source Code Analysis (RKNN API)

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Using the RK3588 Chip NPU: YOLOv8-Pose Example for Image Detection Deployment on Android System and In-Depth Source Code Analysis (RKNN API)

1. Objective of This Article Adapt the YOLOv8-Pose example for the Android platform, providing functionality for pose recognition after selecting an image. Learn the source code and RKNN API through the project. 2. Development Environment Description Host System: Windows 11 Target Device: Android development board equipped with RK3588 chip Core Tools: Android Studio Koala | … Read more

Deploying YOLOv8 on Wildfire RK3588

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Deploying YOLOv8 on Wildfire RK3588

Description Deploying YOLOv8 on Wildfire RK3588, we use yolov8s.pt (downloaded from the YOLOv8 official website) as an example. 1. pt->onnx Do not use the official YOLOv8 code; instead, use the Rockchip YOLOv8 code, available at https://github.com/airockchip/ultralytics_yolov8 After downloading the code, execute the model conversion with the following code: from ultralytics import YOLO model = YOLO('yolov8s.pt') … Read more

Using the RK3588 Chip NPU: Compiling YOLOv8-Pose C Demo in Windows 11 Docker and Running on Development Board

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Using the RK3588 Chip NPU: Compiling YOLOv8-Pose C Demo in Windows 11 Docker and Running on Development Board

The Objective of This Article This article will compile the YOLOv8-Pose C Demo in the RKNN Docker environment and deploy it to the RK3588 development board using the adb tool. Development Environment Description Host System: Windows 11 Target Device: Android development board equipped with the RK3588 chip Core Tools: Docker image containing rknn-toolkit2, rknn_model_zoo, and … Read more

RK3588 Edge Computing Application: Detection of Walnut Ripeness

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RK3588 Edge Computing Application: Detection of Walnut Ripeness

RK3588 Edge Computing Application: Detection of Walnut Ripeness Over the past 60 years, despite the discontinuation of neon tubes, many engineers still have a fondness for them. I created a simulated neon tube clock using 8 LCD screens to experience the aesthetic of retro elements and pay homage to classic designs from the past. The … Read more

Camera Image Acquisition and Recognition Based on YoloV8 and USB Fisheye Camera

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Camera Image Acquisition and Recognition Based on YoloV8 and USB Fisheye Camera

Personal Introduction: I am a graduate student majoring in Communication and Information Systems. My research focuses on intelligent optimization algorithms, drone trajectory planning, fine-tuning large language models, and deployment in specific scenarios. If you have any programming questions or customized needs, feel free to contact me through my public account. 1. Introduction Recently, I received … Read more