MechatronicsBlog / RaspberryPi_EdgeTPU_TFLite_Qt
Edge TPU object detection on Raspberry Pi with Coral USB Accelerator by integrating TensorFlow Lite C++ API and Qt/QML
☆10Updated 5 years ago
Alternatives and similar repositories for RaspberryPi_EdgeTPU_TFLite_Qt:
Users that are interested in RaspberryPi_EdgeTPU_TFLite_Qt are comparing it to the libraries listed below
- Face mask detection on Raspberry Pi 4☆60Updated 3 years ago
- MobileNetV2_YOLOV3 for ncnn framework☆25Updated last year
- A simple logo classifier developed using Maixduino framework and PlatfomIO, to run on K210 MCU on Sipeed's Maix dev board.☆25Updated 5 years ago
- YoloV4 on a bare Raspberry Pi 4 with ncnn framework☆51Updated 9 months ago
- PPE detection of helmets(construction) using Nvidia Deepstream. Model trained using Nvidia TLT.☆11Updated 3 years ago
- Google Coral on the Raspberry Pi 4☆93Updated 4 years ago
- Raspberry Pi, TensorFlow Lite and Qt/QML: image segmentation example☆11Updated 5 years ago
- Use 600 pcs of Masked and No_Masked people, trained and inferenced on Jetson Nano with Yolov3-Tiny☆11Updated 5 years ago
- C++ implementation of a simple MOT using Centroid algo☆28Updated 2 years ago
- A face mask detection using ssd with simplified Mobilenet and RFB or Pelee in Tensorflow 2.1. Training on your own dataset. Can be conve…☆74Updated last year
- Super fast face detection on Raspberry Pi 4☆53Updated 2 years ago
- Yolact running on the ncnn framework on a bare Raspberry Pi 4 with 64 OS, overclocked to 1950 MHz☆12Updated 2 years ago
- TensorFlow Lite segmentation on Raspberry Pi 4 aka Unet at 7.2 FPS with 64-bit OS☆18Updated 2 years ago
- K210 YOLO_V2 FACE DETECTION☆23Updated 5 years ago
- TensorFlow Lite Posenet on bare Raspberry Pi 4 with 64-bit OS at 9.4 FPS☆25Updated 3 months ago
- Exporting YOLOv5 for CPU inference with ONNX and OpenVINO☆36Updated 7 months ago
- TensorFlow Lite, Coral Edge TPU samples (Python/C++, Raspberry Pi/Windows/Linux).☆120Updated 6 months ago
- A github repository for my article about using YOLO network for object detection with Kendryte K210 chip