This project uses TensorFlow Lite with Python on a Raspberry Pi to perform real-time object detection ... the USB Accelerator setup instructions. Run the object detection script using the EdgeTPU ...

If machines could recognise objects the way human beings do, it would be quite interesting. Object detection is a trending topic nowadays. So let us make an object detection camera that can do live ...

Integrating advanced object detection into your projects has become more accessible with the Raspberry Pi AI HAT and YOLO models. This guide outlines a detailed process for setting up the hardware ...

Using Python programming and a Raspberry Pi 3 Model B equipped with the Raspberry Pi Camera Module the project uses OpenCV. Classed as an advanced project on the Hackster.io website you can check ...

Keep in mind that the Raspberry Pi only supports Caffe models, for TensorFlow you’d need to run it on an Ubuntu machine. For the setup that allows you to easily run someone else’s NCS format object ...

Compared with other lightweight models such as Faster RCNN, SSD, and YOLO series, the proposed model also has higher detection accuracy and fewer model parameters. Additionally, the model is deployed ...

To determine if model performance is impacted by training models using low-quality data, a secondary image dataset named MOD-2022 was prepared for object detection and tracking ... dataset and ...

(4) Deployment on Raspberry Pi: The improved lightweight model is deployed on the low-cost ... different categories to evaluate the overall performance of the object detection model. It is a ...