OpenVINO-YoloV3 and YoloV7-ncnn-Raspberry-Pi-4
Maintenance
0/25
Adoption
10/25
Maturity
16/25
Community
25/25
Maintenance
0/25
Adoption
9/25
Maturity
16/25
Community
19/25
Stars: 538
Forks: 165
Downloads: —
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 97
Forks: 20
Downloads: —
Commits (30d): 0
Language: C++
License: BSD-3-Clause
Archived
Stale 6m
No Package
No Dependents
Stale 6m
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No Dependents
About OpenVINO-YoloV3
PINTO0309/OpenVINO-YoloV3
YoloV3/tiny-YoloV3+RaspberryPi3/Ubuntu LaptopPC+NCS/NCS2+USB Camera+Python+OpenVINO
About YoloV7-ncnn-Raspberry-Pi-4
Qengineering/YoloV7-ncnn-Raspberry-Pi-4
YoloV7 for a bare Raspberry Pi using ncnn.
This project helps operations engineers and hobbyists perform real-time object detection on live video feeds or image files using a Raspberry Pi 4. It takes a visual input, like a camera feed or image, and outputs identified objects within that visual, such as cars or people, at decent speeds directly on the device. It's designed for users who want to deploy computer vision solutions on cost-effective, embedded hardware.
embedded-vision
object-detection
real-time-analytics
IOT
edge-computing
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