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v0.4.0

open-mmlab/mmocr

版本发布时间: 2021-12-15 11:40:06

open-mmlab/mmocr最新发布版本:v1.0.1(2023-07-04 15:11:53)

Highlights

  1. We release a new text recognition model - ABINet (CVPR 2021, Oral). With dedicated model design and useful data augmentation transforms, ABINet achieves the best performance on irregular text recognition tasks. Check it out!
  2. We are also working hard to fulfill the requests from our community. OpenSet KIE is one of the achievements, which extends the application of SDMGR from text node classification to node-pair relation extraction. We also provide a demo script to convert WildReceipt to open set domain, though it may not take full advantage of the OpenSet format. For more information, read our tutorial.
  3. APIs of models can be exposed through TorchServe. Docs

Breaking Changes & Migration Guide

Postprocessor

Some refactoring processes are still going on. For all text detection models, we unified their decode implementations into a new module category, POSTPROCESSOR, which is responsible for decoding different raw outputs into boundary instances. In all text detection configs, the text_repr_type argument in bbox_head is deprecated and will be removed in the future release.

Migration Guide: Find a similar line from detection model's config:

text_repr_type=xxx,

And replace it with

postprocessor=dict(type='{MODEL_NAME}Postprocessor', text_repr_type=xxx)),

Take a snippet of PANet's config as an example. Before the change, its config for bbox_head looks like:

    bbox_head=dict(
        type='PANHead',
        text_repr_type='poly',
        in_channels=[128, 128, 128, 128],
        out_channels=6,
        loss=dict(type='PANLoss')),

Afterwards:

    bbox_head=dict(
    type='PANHead',
    in_channels=[128, 128, 128, 128],
    out_channels=6,
    loss=dict(type='PANLoss'),
    postprocessor=dict(type='PANPostprocessor', text_repr_type='poly')),

There are other postprocessors and each takes different arguments. Interested users can find their interfaces or implementations in mmocr/models/textdet/postprocess or through our api docs.

New Config Structure

We reorganized the configs/ directory by extracting reusable sections into configs/_base_. Now the directory tree of configs/_base_ is organized as follows:

_base_
├── det_datasets
├── det_models
├── det_pipelines
├── recog_datasets
├── recog_models
├── recog_pipelines
└── schedules

Most of model configs are making full use of base configs now, which makes the overall structural clearer and facilitates fair comparison across models. Despite the seemingly significant hierarchical difference, these changes would not break the backward compatibility as the names of model configs remain the same.

New Features

Refactoring

Docs

Enhancements

Bug Fixes

New Contributors

Full Changelog: https://github.com/open-mmlab/mmocr/compare/v0.3.0...v0.4.0

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