Only use CPU to run Yolov5 in real time on the drone (implemented by OpenVINO) (Part 2) - Code World

Only use CPU to run Yolov5 in real time on the drone (implemented by OpenVINO) (Part 2)

News 2023-06-21 21:33:49 views: null

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Origin blog.csdn.net/bruce__ray/article/details/131144164

Only use CPU to run Yolov5 in real time on the drone (implemented by OpenVINO) (Part 2)

Run Yolov5 (implemented by OpenVINO) in real time using only the CPU on the UAV (Part 1)

Only use CPU to run Yolov5 in real time on the drone (implemented by OpenVINO) (Part 2)

Only use CPU to run Yolov5 in real time on the drone (implemented by OpenVINO) (Part 2)

Project 2: Use Yolov5 and deepsort to track vehicles and pedestrians, and calculate the speed and acceleration of the target in real time (with the function of detecting overspeed)

(Common bug in Yolov5) RuntimeError: “slow_conv2d_cpu“ not implemented for 'Half' problem solved

Run yolov5 on CPU (detailed steps + suitable for getting started)

AI Project 6: Deploying openvino based on the CPU version of YOLOV5

Print information on the YOLOv5 real-time detection screen

Real-time coordinate printing of YOLOv5 recognition target

Real-time mask detection using YOLOv5

My open source project - Use OnnxRuntime to deploy RTMPose on the CPU side for real-time 2D pose estimation

The ten coolest drone projects in 2020 (part 2)

YOLOv5 (target detection part does not include instance segmentation) -nncf quantification, evaluation, and openvino reasoning on the python side

OpenVINO™ to run the GPT-2 model

YOLOv5 Series 2. Use yolov5 to identify your own data

RuntimeError: “unfolded2d_copy“ not implemented for ‘Half‘ 解决 yolov5 deepsort

The solution of vue that the same browser only allows one account to be logged in at the same time - real project use

Openvino model conversion and deployment of yoloV5

yolov5 online detection target detection webpage real-time recognition python target detection flask

Jetson AGX Xavier implements TensorRT to accelerate YOLOv5 for real-time detection

C++ reads the yolov5 model for target detection (reads the real-time monitoring of the camera)

Deployment of yolov5 model (.pt) on RK3588(S) (real-time camera detection)

[Selected] Improved YOLOv5 lane line real-time segmentation system integrating Seg head network

yolov5 (cpu) configuration

The use of the OLED display of the expansion board equipped with JetsonNano (real-time display of IP, memory, CPU, etc.)

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[openvino+Raspberry Pi] Real-time camera face detection

This article teaches you to use the leased GPU platform to run yolov5

Use yolov5s.pt weights, combined with opencv, to achieve real-time detection

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