Qengineering/YoloFastestV2-ncnn-Raspberry-Pi-4
YoloFastestV2 for a bare Raspberry Pi 4
This project helps you identify and locate multiple objects within images or video feeds using a Raspberry Pi 4. It takes visual data as input and outputs bounding boxes around detected objects with their labels. This is ideal for hobbyists, educators, or small-scale automation enthusiasts building custom vision systems on low-cost hardware.
No commits in the last 6 months.
Use this if you need fast, local object detection on a Raspberry Pi 4 for tasks like security monitoring, robotics, or interactive displays, without needing cloud services.
Not ideal if you require extremely high accuracy for very small objects, or if you're working with very large, high-resolution images.
Stars
40
Forks
7
Language
C++
License
BSD-3-Clause
Category
Last pushed
Jun 21, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/Qengineering/YoloFastestV2-ncnn-Raspberry-Pi-4"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
PINTO0309/OpenVINO-YoloV3
YoloV3/tiny-YoloV3+RaspberryPi3/Ubuntu LaptopPC+NCS/NCS2+USB Camera+Python+OpenVINO
RangiLyu/nanodet
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) /...
dog-qiuqiu/MobileNet-Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops...
Qengineering/Face-Recognition-Jetson-Nano
Recognize 2000+ faces on your Jetson Nano with database auto-fill and anti-spoofing
Qengineering/YoloV8-NPU
YoloV8 NPU for the RK3566/68/88