caixiongjiang/FastSegFormer
[ISSN 0168-1699, COMPUT ELECTRON AGR 2024] FastSegFormer: A knowledge distillation-based method for real-time semantic segmentation of surface defects in navel oranges.
This project helps agricultural quality control specialists quickly identify surface defects on navel oranges. By taking images or live video of oranges, it outputs segmented images highlighting defective areas in real-time. This allows for automated, high-speed inspection on a production line.
No commits in the last 6 months.
Use this if you need to automatically and rapidly detect surface defects on navel oranges using image or video input, especially in a high-throughput environment like a sorting line.
Not ideal if you need to detect internal defects or analyze fruit types other than navel oranges, as it's specifically trained for surface issues on this particular fruit.
Stars
22
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 06, 2024
Commits (30d)
0
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