dog-qiuqiu/MobileNet-Yolo
MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:
This project offers extremely fast and small object detection models that can identify objects or faces in images and video, even on mobile phones and low-power devices. It takes in an image or video feed and outputs bounding boxes around detected objects or faces, including key facial points. This is useful for anyone building applications that need real-time visual analysis on edge devices, like security system designers, mobile app developers, or robotics engineers.
1,748 stars. No commits in the last 6 months.
Use this if you need to detect objects or faces rapidly and accurately using devices with limited processing power, such as mobile phones or embedded systems.
Not ideal if you require the absolute highest detection accuracy and have ample computing resources (like powerful GPUs) available for more complex models.
Stars
1,748
Forks
280
Language
C
License
—
Category
Last pushed
Feb 06, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/dog-qiuqiu/MobileNet-Yolo"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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) /...
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
Qengineering/Face-Recognition-Raspberry-Pi-64-bits
Recognize 2000+ faces on your Raspberry Pi 4 with database auto-fill and anti-spoofing