v0.3.0: Multi-backend Support, Additional Models, Better Visualizations, and many more
We are excited to release LayoutParser v0.3.0, with a lot of exciting updates and functional improvements.
New Features
- The biggest change in this version is that LayoutParser now supports multiple deep learning backends: Detectron2, effdet, and paddledetection. This allows for more flexible usage of the
layoutparser
library, and makes it easier for implementing customized layout models in the future. #54 #67 - Additionally, the newly added
AutoModel
and improved model configuration parsing makes it easier load and use the layout detection models. #69- e.g,
model = lp.AutoLayoutModel("lp://efficientdet/PubLayNet")
.
- e.g,
- To support this multi-backend framework, we implement the dynamic importing mechanism as well as better ways for installing
layoutparser
and the needed dependencies (see instructions). #65 #68 - And now
layoutparser
supports directly loading PDF files into aslayout
objects: #71import layoutparser as lp pdf_layout, pdf_images = lp.load_pdf("path/to/pdf", load_images=True) lp.draw_box(pdf_images[0], pdf_layout[0])
- To support more flexible processing of the layout objects, a set of new toolkits are available: #72
import layout parser as lp page_layout = lp.load_pdf("tests/fixtures/io/example.pdf")[0] pdf_lines = lp.simple_line_detection(page_layout)
New Models
- Add MFD model that can detect (display) equation regions within scientific documents #59