Object detection is typically performed using well-known algorithms such as R-CNN and Fast R-CNN and YOLO. YOLO is particularly popular for achieving real-time object detection owing to its high accuracy and speed.
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✔️ HDMI 2.1 output (up to 8K@60fps), HDMI 2.0 input (up to 4K@60fps)
We tested YOLOv5 using our Blade 3 board to assess its performance and demonstrate its effectiveness.
In this video, we'll show you how to use our product to do amazing RK YOLOv5 Object Detection that will blow your mind.
Whether you're a beginner or a seasoned AI enthusiast, this video is for you with our demo for reference. So, let's get started!🤩
The topics will be covered:
0:00 Sneak peek of Object Detection
0:07 Start
0:13 Things to prepare
0:27 Connect the device
0:58 Run RK YOLOv5 Demo to Capture Objects in Real-time
1:56 Object Detection for Videos and Streaming Sources
#yolo #yolodeeplearning #yolov5 #yoloobjectdetection #yolopython #yoloopencv #rockchip #ai #aiobjectdetection #machinelearning #objectdetection
Learning resources of this video:
RK YOLOv5 TensorRT benchmark: [ Ссылка ]
Real-time object detection tutorials: [ Ссылка ]
Object detection for videos: [ Ссылка ]
Mixtile Blade 3 board: [ Ссылка ]
Want more technical support? Join Mixtile Community: [ Ссылка ]
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