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https://github.com/qengineering/qengineering

Machine vision apps
https://github.com/qengineering/qengineering
deep-learning face-detection jetson-nano mnn ncnn paddle raspberry-pi-4 tensorflow
Last synced: 4 months ago
JSON representation
Machine vision apps
Host: GitHub
URL: https://github.com/qengineering/qengineering
Owner: Qengineering
Created: 2021-01-17T10:38:52.000Z (about 4 years ago)
Default Branch: main
Last Pushed: 2024-08-08T10:50:58.000Z (6 months ago)
Last Synced: 2024-10-11T02:02:13.558Z (4 months ago)
Topics: deep-learning, face-detection, jetson-nano, mnn, ncnn, paddle, raspberry-pi-4, tensorflow
Homepage: https://qengineering.eu/
Size: 214 KB
Stars: 32
Watchers: 3
Forks: 8
Open Issues: 1
Metadata Files:
- Readme: README.md
Awesome Lists containing this project

README

        ![output image]( https://qengineering.eu/github/GitHubLogo.jpg )

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## **[YoloCam](https://github.com/Qengineering/YoloCam)**

![output image]( https://qengineering.eu/github/YoloCamGitHubSocialSmall.jpg ) ![output image]( https://qengineering.eu/github/YoloCamGitHubSocialSmallScreen.jpg )


A Raspberry Pi 4, 3 or Zero 2, with stand-alone AI object recognition, browser-based live streaming, email, cloud storage, GPIO and URL event triggers.


#### **[YoloIP](https://github.com/Qengineering/YoloIP)** 

![output image]( https://qengineering.eu/github/YoloIPGitHubSocialSmall.jpg ) ![output image]( https://qengineering.eu/github/YoloIPGitHubSocialSmallScreen.jpg )


A Raspberry Pi 4 or 5, with stand-alone AI, supports multiple IP surveillance cameras.

---------

## Table of Contents

- ### Deep Learning

  * **Classification**

    + [TensorFlow Lite Raspberry Pi zero](https://github.com/Qengineering/TensorFlow_Lite_Classification_RPi_zero)

    + [TensorFlow Lite Raspberry Pi 32](https://github.com/Qengineering/TensorFlow_Lite_Classification_RPi_32-bits)

    + [TensorFlow Lite Raspberry Pi 64](https://github.com/Qengineering/TensorFlow_Lite_Classification_RPi_64-bits)

    + [TensorFlow Lite Jetson Nano](https://github.com/Qengineering/TensorFlow_Lite_Classification_Jetson-Nano)

    + [ncnn ShuffleNetV2 Raspberry Pi](https://github.com/Qengineering/ShuffleNetV2-ncnn)

    + [ncnn SqueezeNet Raspberry Pi](https://github.com/Qengineering/SqueezeNet-ncnn)

  * **SSD**



      Raspberry Pi 4/5

    + [TensorFlow Lite Raspberry Pi 32](https://github.com/Qengineering/TensorFlow_Lite_SSD_RPi_32-bits)

    + [TensorFlow Lite Raspberry Pi 64](https://github.com/Qengineering/TensorFlow_Lite_SSD_RPi_64-bits)

    + [OpenCV MobileNetV1_SSD Caffe Raspberry Pi 64](https://github.com/Qengineering/MobileNetV1_SSD_OpenCV_Caffe)

    + [OpenCV MobileNetV1_SSD TensorFlow Raspberry Pi 64](https://github.com/Qengineering/MobileNet_SSD_OpenCV_TensorFlow)

    + [ncnn Rfcn Raspberry Pi 64](https://github.com/Qengineering/Rfcn_ncnn)

    + [ncnn Faster RCNN Raspberry Pi 64](https://github.com/Qengineering/Faster_RCNN_ncnn)

    + [ncnn PeeleeNet Raspberry Pi 64](https://github.com/Qengineering/PeleeNet_SSD)

    + [ncnn NanoDet Raspberry Pi 64](https://github.com/Qengineering/NanoDet-ncnn-Raspberry-Pi-4)

    + [ncnn NanoDet Plus Raspberry Pi 64](https://github.com/Qengineering/NanoDetPlus-ncnn-Raspberry-Pi-4)

    + [ncnn PP-PicoDet Raspberry Pi 64](https://github.com/Qengineering/PP-PicoDet-ncnn-Raspberry-Pi-4)

    + [ncnn YoloFastestV2 Raspberry Pi 64](https://github.com/Qengineering/YoloFastestV2-ncnn-Raspberry-Pi-4)

    + [ncnn YoloX Raspberry Pi 64](https://github.com/Qengineering/YoloX-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV2 Raspberry Pi 64](https://github.com/Qengineering/YoloV2-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV3 Raspberry Pi 64](https://github.com/Qengineering/YoloV3-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV4 Raspberry Pi 64](https://github.com/Qengineering/YoloV4-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV5 Raspberry Pi 64](https://github.com/Qengineering/YoloV5-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV6 Raspberry Pi 64](https://github.com/Qengineering/YoloV6-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV7 Raspberry Pi 64](https://github.com/Qengineering/YoloV7-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV8 Raspberry Pi 64](https://github.com/Qengineering/YoloV8-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV9 Raspberry Pi 64](https://github.com/Qengineering/YoloV9-ncnn-Raspberry-Pi-4)

    + [ncnn YoloV10 Raspberry Pi 64](https://github.com/Qengineering/YoloV10-ncnn-Raspberry-Pi-4)



      Jetson Nano

    + [TensorFlow Lite Jetson Nano](https://github.com/Qengineering/TensorFlow_Lite_SSD_Jetson-Nano)

    + [Darknet YoloV4 Jetson Nano](https://github.com/Qengineering/YoloV4-Darknet-Jetson-Nano)

    + [ncnn NanoDet Jetson Nano](https://github.com/Qengineering/NanoDet-ncnn-Jetson-Nano)

    + [ncnn NanoDet Plus Jetson Nano](https://github.com/Qengineering/NanoDetPlus-ncnn-Jetson-Nano)

    + [ncnn PP-PicoDet Jetson Nano](https://github.com/Qengineering/PP-PicoDet-ncnn-Jeston-Nano)

    + [ncnn YoloFastetsV2 Jetson Nano](https://github.com/Qengineering/YoloFastest-ncnn-Jetson-Nano)

    + [ncnn YoloX Jetson Nano](https://github.com/Qengineering/YoloX-ncnn-Jetson-Nano)

    + [ncnn YoloV2 Jetson Nano](https://github.com/Qengineering/YoloV2-ncnn-Jetson-Nano)

    + [ncnn YoloV3 Jetson Nano](https://github.com/Qengineering/YoloV3-ncnn-Jetson-Nano)

    + [ncnn YoloV4 Jetson Nano](https://github.com/Qengineering/YoloV4-ncnn-Jetson-Nano)

    + [ncnn YoloV5 Jetson Nano](https://github.com/Qengineering/YoloV5-ncnn-Jetson-Nano)

    + [ncnn YoloV6 Jetson Nano](https://github.com/Qengineering/YoloV6-ncnn-Jetson-Nano)

    + [ncnn YoloV7 Jetson Nano](https://github.com/Qengineering/YoloV7-ncnn-Jetson-Nano)



      TensorRT

    + [TensorRT YoloV8.2 Jetson (Orin) Nano](https://github.com/Qengineering/YoloV8-TensorRT-Jetson_Nano)



      NPU RK3566/68/88 (Radxa Zero 3, Rock 5, Orange Pi 5, Rock5c)

    + [NPU PP YoloE](https://github.com/Qengineering/PPYoloE-NPU)

    + [NPU YoloX](https://github.com/Qengineering/YoloX-NPU)

    + [NPU YoloV5](https://github.com/Qengineering/YoloV5-NPU)

    + [NPU YoloV6](https://github.com/Qengineering/YoloV6-NPU)

    + [NPU YoloV7](https://github.com/Qengineering/YoloV7-NPU)

    + [NPU YoloV8](https://github.com/Qengineering/YoloV8-NPU)

    + [NPU YoloV10](https://github.com/Qengineering/YoloV10-NPU)

  * **Tracking**

    + [ByteTrack with labels](https://github.com/Qengineering/ByteTrack_with_labels)

    + [Traffic counter camera Rpi 64](https://github.com/Qengineering/Traffic-Counter-RPi_64-bit) 

    + [ncnn YoloX + Tracking Rpi 64](https://github.com/Qengineering/YoloX-Tracking-ncnn-RPi_64-bit)

    + [ncnn NanoDet + Tracking Rpi 64](https://github.com/Qengineering/NanoDet-Tracking-ncnn-RPi_64-bit)

    + [Tensorflow Lite + Tracking Rpi 64](https://github.com/Qengineering/TensorFlow_Lite-Tracking-RPi_64-bit)

  * **Segmentation**

    + [TensorFlow Lite Raspberry Pi 32](https://github.com/Qengineering/TensorFlow_Lite_Segmentation_RPi_32-bit)

    + [TensorFlow Lite Raspberry Pi 64](https://github.com/Qengineering/TensorFlow_Lite_Segmentation_RPi_64-bit)

    + [TensorFlow Lite Jetson Nano](https://github.com/Qengineering/TensorFlow_Lite_Segmentation_Jetson-Nano)

    + [ncnn YoloV5 segmentation Rpi 64](https://github.com/Qengineering/YoloV5-segmentation-ncnn-RPi4)

    + [ncnn Yolact Raspberry Pi](https://github.com/Qengineering/Yolact-ncnn-Raspberry-Pi-4)

    + [NPU YoloV5-seg](https://github.com/Qengineering/YoloV5-seg-NPU)    

    + [NPU YoloV8-seg](https://github.com/Qengineering/YoloV8-seg-NPU)    

  * **Pose**

    + [TensorFlow Lite Raspberry Pi 32](https://github.com/Qengineering/TensorFlow_Lite_Pose_RPi_32-bits)

    + [TensorFlow Lite Raspberry Pi 64](https://github.com/Qengineering/TensorFlow_Lite_Pose_RPi_64-bits)

    + [TensorFlow Lite Jetson Nano](https://github.com/Qengineering/TensorFlow_Lite_Pose_Jetson-Nano)

    + [ncnn Raspberry Pi 64](https://github.com/Qengineering/ncnn_Pose_RPi_64-bits)   

  * **Face detection**

    + [MNN Ultra Raspberry Pi 64](https://github.com/Qengineering/Face-detection-Raspberry-Pi-32-64-bits/tree/master/MNN)

    + [ncnn Ultra Raspberry Pi 64](https://github.com/Qengineering/Face-detection-Raspberry-Pi-32-64-bits/tree/master/ncnn)

    + [OpenCV Ultra Raspberry Pi 64](https://github.com/Qengineering/Face-detection-Raspberry-Pi-32-64-bits/tree/master/OpenCV)

    + [ncnn LFFD Raspberry Pi 64](https://github.com/Qengineering/LFFD-ncnn-Raspberry-Pi-4)

    + [MNN LFFD Raspberry Pi 64](https://github.com/Qengineering/LFFD-MNN-Raspberry-Pi-4)

    + [ncnn CenterFace Raspberry Pi 64](https://github.com/Qengineering/CenterFace-ncnn-Raspberry-Pi-4)

    + [ncnn LFFD Jetson Nano](https://github.com/Qengineering/LFFD-ncnn-Jetson-Nano)

    + [MNN LFFD Jetson Nano](https://github.com/Qengineering/LFFD-MNN-Jetson-Nano)

    + [ncnn CenterFace Jetson Nano](https://github.com/Qengineering/CenterFace-ncnn-Jetson-Nano)

    + [ncnn YoloV5 face Raspberry Pi 64](https://github.com/Qengineering/YoloV5-face-ncnn-RPi4)

    * Face detection with landmarks

      + [ncnn Ultra Raspberry Pi](https://github.com/Qengineering/Face-detection-Landmark-Raspberry-Pi-32-64-bits)

  * **Face mask detection**

    + [ncnn + Paddle Raspberry Pi](https://github.com/Qengineering/Face-Mask-Detection-Raspberry-Pi-64-bits)

    + [ncnn + Paddle Jetson Nano](https://github.com/Qengineering/Face-Mask-Detection-Jetson-Nano)

    + [TensorFlow Raspberry Pi](https://github.com/Qengineering/TensorFlow_Lite_Face_Mask_RPi_64-bits)

    + [TensorFlow Jetson Nano](https://github.com/Qengineering/TensorFlow_Lite_Face_Mask_Jetson-Nano)

  * **Face recognition**

    + [ncnn Raspberry Pi](https://github.com/Qengineering/Face-Recognition-Raspberry-Pi-64-bits)

    + [ncnn Jetson Nano](https://github.com/Qengineering/Face-Recognition-Jetson-Nano)

    * Face recognition with mask

      + [ncnn Jetson Nano](https://github.com/Qengineering/Face-Recognition-with-Mask-Jetson-Nano)

  * **OCR**

    + [PaddleOCR-Lite License plate RPi](https://github.com/Qengineering/PaddleOCR-Lite-License)

    + [PaddleOCR-Lite Document scanner RPi](https://github.com/Qengineering/PaddleOCR-Lite-Document)

    + [OpenCV detect text in image RPi](https://github.com/Qengineering/OpenCV_OCR_Detect_Text)

    + [OpenCV recognize text with deep learning RPi](https://github.com/Qengineering/OpenCV_OCR_DNN)

    + [OpenCV recognize text with tesseract RPi](https://github.com/Qengineering/OpenCV_OCR_Tesseract)

  * **Parking** 

    + [XACTAI - OCR - License plate](https://github.com/xactai/ALPR_1.5_Public/tree/master/ALPR_1.5)

  * **Super-resolution**

    + [real ESRGAN ncnn Raspberry Pi 4 ](https://github.com/Qengineering/Real-ESRGAN-ncnn-Raspberry-Pi-4)

    + [realsr ncnn Jetson Nano](https://github.com/Qengineering/realsr-ncnn-Jetson-Nano)

  * **Face reconstruction**

    + [GFPGAN ncnn Raspberry Pi 4 ](https://github.com/Qengineering/GFPGAN-ncnn-Raspberry-Pi-4)

  * **Age Gender estimation**

    + [OpenCV Raspberry Pi](https://github.com/Qengineering/Age-Gender-OpenCV-Raspberry-Pi-4)

  * **Head pose estimation**

    + [ncnn Ultra Raspberry Pi 64](https://github.com/Qengineering/Head-Pose-ncnn-Raspberry-Pi-4)

  * **Hand pose estimation**

    + [ncnn NanoDet Raspberry Pi 64](https://github.com/Qengineering/Hand-Pose-ncnn-Raspberry-Pi-4)

  * **Colorization**

    + [ncnn Colorization Raspberry Pi 64](https://github.com/Qengineering/ncnn-Colorization_Raspberry-Pi-4)

  * **QR and bar code**

    + [ZBar Raspberry Pi](https://github.com/Qengineering/QR_scanner_Raspberry_Pi)

- ### Wheels

  * **TensorFlow**

    + [Raspberry Pi 32](https://github.com/Qengineering/TensorFlow-Raspberry-Pi)

    + [Raspberry Pi 64](https://github.com/Qengineering/TensorFlow-Raspberry-Pi_64-bit)

    + [Jetson Nano](https://github.com/Qengineering/TensorFlow-JetsonNano)

  * **TensorFlow Lite**

    + [Raspberry Pi 64](https://github.com/Qengineering/TensorFlow-Lite-Raspberry-Pi_64-bit)

    + [Jetson Nano](https://github.com/Qengineering/TensorFlow-Lite-Raspberry-Pi_64-bit)

  * **TensorFlow Addons**

    + [Raspberry Pi 64](https://github.com/Qengineering/TensorFlow-Addons-Raspberry-Pi_64-bit)

    + [Jetson Nano](https://github.com/Qengineering/TensorFlow-Addons-Jetson-Nano)

  * **PyTorch**

    + [Raspberry Pi 64](https://github.com/Qengineering/PyTorch-Raspberry-Pi-64-OS)

    + [Jetson Nano](https://github.com/Qengineering/PyTorch-Jetson-Nano)

  * **PaddlePaddle**

    + [Raspberry Pi 64](https://github.com/Qengineering/Paddle-Raspberry-Pi)

    + [Jetson Nano](https://github.com/Qengineering/Paddle-Jetson-Nano)

  * **TensorRT**

    + [Jetson Nano Ubuntu 20.04](https://github.com/Qengineering/Jetson-Nano-Ubuntu-20-image)

  * **OpenCV**

    + [Raspberry Pi 32](https://github.com/Qengineering/Install-OpenCV-Raspberry-Pi-32-bits)

    + [Raspberry Pi 64](https://github.com/Qengineering/Install-OpenCV-Raspberry-Pi-64-bits)  

    + [Jetson Nano](https://github.com/Qengineering/Install-OpenCV-Jetson-Nano)

- ### Miscellaneous

  * **rtop**

    + [rtop Ubuntu](https://github.com/Qengineering/rtop-Ubuntu)

    + [rtop KDE](https://github.com/Qengineering/rtop-KDE) 

  * OpenCV

    + [libcamera C++ API wrapper Bullseye 64](https://github.com/Qengineering/LCCV)

    * GStreamer

      * Buster

        + [GStreamer 1.18.4 + OpenCV Raspberry Pi 32](https://github.com/Qengineering/GStreamer-1.18.4-RPi_32-bits)

        + [GStreamer 1.18.4 + OpenCV Raspberry Pi 64](https://github.com/Qengineering/GStreamer-1.18.4-RPi_64-bits)

      * Bullseye 

        + [Libcamera + OpenCV on Raspberry Pi 32](https://github.com/Qengineering/Libcamera-OpenCV-RPi-Bullseye-32OS)

        + [Libcamera + OpenCV on Raspberry Pi 64](https://github.com/Qengineering/Libcamera-OpenCV-RPi-Bullseye-64OS)

    + [Multithread cameras with OpenCV](https://github.com/Qengineering/Multithread-Camera-OpenCV)

    + [RTSP with OpenCV](https://github.com/Qengineering/RTSP-with-OpenCV)

    + [Examples Raspberry Pi 64](https://github.com/Qengineering/OpenCV-Livecam-Raspberry-Pi)

    + [Qt5 RPi 64 + Jetson Nano](https://github.com/Qengineering/Qt5-OpenCV-Raspberry-Pi-Jetson-Nano)

    + [Blur detection](https://github.com/Qengineering/Blur-detection-with-FFT-in-C)

    + [Fast background substraction](https://github.com/Qengineering/Fast-Background-Substraction)

  * Sensors

    + [DHT22 sensor](https://github.com/Qengineering/DHT22-Raspberry-Pi)

  * Caffe

    + [cuDNN 8.0 + CUDA 10.3 WeiLui SSD Fork + Configuration files RPi, Jetson](https://github.com/Qengineering/caffe)

  * NPU

    + [RKNN model zoo](https://github.com/Qengineering/rknn_model_zoo)

- ### Images

![output image]( https://qengineering.eu/github/SDcard32GB_small.jpg ) [Raspberry Pi 4 **Bullseye** 64-bit OS with several frameworks and deep-learning examples](https://github.com/Qengineering/RPi-Bullseye-DNN-image)



![output image]( https://qengineering.eu/github/SDcard16GB_small.jpg ) [Raspberry Pi 4 Buster 64-bit OS with several frameworks and deep-learning examples](https://github.com/Qengineering/RPi-image)



![output image]( https://qengineering.eu/github/SDcard16GBZero2small.jpg ) [Raspberry Pi **Zero 2 W 64-bit** OS image with OpenCV, TensorFlow Lite and ncnn](https://github.com/Qengineering/RPi_64-bit_Zero-2-image)



![output image]( https://qengineering.eu/github/SDcard16GB_banana.jpg ) [Banana Pi M2 Zero image **with OV5640** camera and OpenCV](https://github.com/Qengineering/BananaPi-M2-Zero-OV5640)



![output image]( https://qengineering.eu/github/SDcard32GB_RockPi5.jpg ) [Rock 5 with OpenCV, TNN, ncnn and **NPU**](https://github.com/Qengineering/Rock-5-image)



![output image]( https://qengineering.eu/github/RockPi5_Ubuntu_22.jpg ) [Rock 5 with **Ubuntu 22.04**, OpenCV, ncnn and **NPU**](https://github.com/Qengineering/Rock-5-Ubuntu-22-image)



![output image]( https://qengineering.eu/github/RadxaZero3_Ubuntu_22.jpg ) [Radxa Zero 3 with **Ubuntu 22.04**, OpenCV, ncnn and **NPU**](https://github.com/Qengineering/Radxa-Zero-3-NPU-Ubuntu22)



![output image]( https://qengineering.eu/github/SDcard32GB_smallJetson.jpg ) [A Jetson Nano image with OpenCV, TensorFlow and PyTorch](https://github.com/Qengineering/Jetson-Nano-image)



![output image]( https://qengineering.eu/github/SDcard32GBJetsonUB20small.jpg ) [A Jetson Nano - **Ubuntu 20.04** image with OpenCV, TensorFlow and PyTorch](https://github.com/Qengineering/Jetson-Nano-Ubuntu-20-image)



- ### Applications

![output image]( https://qengineering.eu/github/SDcardMotion.jpg ) [RPi z2, 3 or 4 motion surveillance camera with email notification and gdrive storage](https://github.com/Qengineering/RPiMotionCam)



![output image]( https://qengineering.eu/github/SDcardDNN.jpg ) [**YoloCam**, the cheapest AI-powered camera with email notification, gdrive storage and GPIO output](https://github.com/Qengineering/YoloCam)



![output image]( https://qengineering.eu/github/SDcardYoloIP.jpg ) [**YoloIP**, the cheapest AI-powered machine, supports multiple IP surveillance cameras](https://github.com/Qengineering/YoloIP)



![Qengineering's github stats](https://github-readme-stats.vercel.app/api?username=Qengineering&count_private=true&show_icon=true&card_width=400&bg_color=00000000&title_color=005E2C&text_color=949CA5&show_icons=true&hide_border=true&icon_color=00BE33)


 

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