Search FoxAI
AI Models 257
- ppt-wc-uniform-newlex-eus-after-100mb-packed-bfdiso_seed3407↗
francesca9805
- PP-DocLayout_plus-L↗
PaddlePaddle
A higher-precision layout area localization model trained on a self-built dataset containing Chinese and English papers, PPT, multi-layout magazines, contracts, books, exams, ancient books and research reports using RT-DETR-L. The layout detection model includes 20 common categories: document title, paragraph title, text, page number, abstract, table, references, footnotes, header, footer, algorithm, formula, formula number, image, table, seal, figure_table title, chart, and sidebar text and lists of references. The key metrics are as follow: **Note**: the evaluation set of the above precision indicators is the self built version sub area detection data set, including Chinese and English papers, magazines, newspapers, research reports PPT、 1000 document type pictures such as test papers and textbooks. You can also integrate the model inference of the layout detection module into your project. Before running the following code, please download the sample image to your local machine.
- ita-latn-100mb-after-ppt-Dp-10mb-packed-bfdiso-ckpt500_seed455↗
francesca9805
- hin-deva-10mb-ppt-Dp-100mb-packed-bfdiso_seed455↗
francesca9805
- arb-arab-10mb-after-ppt-Dp-100mb-packed-bfdiso-ckpt500_seed10↗
francesca9805
- urd-arab-100mb-after-ppt-mp-struct-core-100mb-ckpt500_seed3407↗
francesca9805
- ppt-pythia-1b-appendix-frequent-permuted-seed3407-stage2↗
qing-yao
- dan-latn-100mb-after-ppt-mp-struct-100mb-ckpt500_seed455↗
francesca9805
- ita-latn-10mb-after-ppt-Dp-10mb-packed-bfdiso-ckpt500_seed455↗
francesca9805
- eng-latn-100mb-after-ppt-mp-struct-bcc-100mb-ckpt500_seed455↗
francesca9805