YoloV7-ncnn-Raspberry-Pi-4 and YoloFastestV2-ncnn-Raspberry-Pi-4

These are **competitors**, as both projects offer different versions of YOLO (YoloV7 and YoloFastestV2) optimized for bare Raspberry Pi 4 using the ncnn inference framework, requiring users to choose one based on their specific needs for accuracy versus speed.

YoloV7-ncnn-Raspberry-Pi-4

Emerging

YoloFastestV2-ncnn-Raspberry-Pi-4

Emerging

Maintenance 0/25

Adoption 9/25

Maturity 16/25

Community 19/25

Maintenance 0/25

Adoption 7/25

Maturity 16/25

Community 15/25

Stars: 97

Forks: 20

Downloads: —

Commits (30d): 0

Language: C++

License: BSD-3-Clause

Stars: 40

Forks: 7

Downloads: —

Commits (30d): 0

Language: C++

License: BSD-3-Clause

Stale 6m No Package No Dependents

About YoloV7-ncnn-Raspberry-Pi-4

Qengineering/YoloV7-ncnn-Raspberry-Pi-4

YoloV7 for a bare Raspberry Pi using ncnn.

About YoloFastestV2-ncnn-Raspberry-Pi-4

Qengineering/YoloFastestV2-ncnn-Raspberry-Pi-4

YoloFastestV2 for a bare Raspberry Pi 4

Related comparisons

YoloV7-ncnn-Raspberry-Pi-4 and YoloV8-ncnn-Raspberry-Pi-4 YoloV7-ncnn-Raspberry-Pi-4 and YoloX-Tracking-ncnn-RPi_64-bit YoloV7-ncnn-Raspberry-Pi-4 and YoloV5-ncnn-Raspberry-Pi-4 YoloV7-ncnn-Raspberry-Pi-4 and YoloV8-ncnn-Raspberry-Pi-4 YoloV7-ncnn-Raspberry-Pi-4 and YoloX-Tracking-ncnn-RPi_64-bit YoloV7-ncnn-Raspberry-Pi-4 and YoloV6-ncnn-Raspberry-Pi-4

Scores updated daily from GitHub, PyPI, and npm data. How scores work