linhdb-2149
linhdb-2149
**Describe the feature** Paper Title: SVTR: Scene Text Recognition with a Single Visual Model Paper link: https://arxiv.org/pdf/2205.00159v2.pdf **Motivation** This new method provide interesting approach to stroke-typed language such as Chinese/Japanese......
Are quantization formulas (specially symmetric quantization formula) the same as reported in paper? https://arxiv.org/pdf/2002.08679.pdf Paper:  Docs: https://github.com/openvinotoolkit/nncf/blob/4c7a0045abd557af13eb9b6386f88f5d5d30a2ff/docs/compression_algorithms/Quantization.md  According to the paper, there are no rescale ($*\frac{scale}{levelhigh}$) after rounding....
Several images are still visible but return NoneType when read Ex: 2711