MinerU, an open-source tool for converting complex documents into machine-readable formats, has seen active development with a focus on improving PDF parsing accuracy and performance optimization.
Recent issues and pull requests (PRs) highlight ongoing challenges with PDF parsing, particularly in table recognition and handling complex layouts. Key issues include #637 (unsupported UTF-32 encoding), #633 (missing content in tables), and #619 (OOM error in CUDA mode). These issues reflect user demand for robust document processing capabilities.
Xiaomeng Zhao (myhloli)
version.py
, merged PRs on figure-footnote relations, refactored pdf_extract_kit
, added language support.icecraft
drunkpig
Focusshang
quyuan
LollipopsAndWine (linfeng)
dt-yy
wangbinDL
Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 12 | 44 | 25 | 1 | 1 |
14 Days | 42 | 51 | 102 | 1 | 1 |
30 Days | 93 | 76 | 239 | 7 | 1 |
All Time | 386 | 260 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
Developer | Avatar | Branches | PRs | Commits | Files | Changes |
---|---|---|---|---|---|---|
drunkpig | 2 | 7/4/3 | 6 | 78 | 21433 | |
linfeng (LollipopsAndWine) | 1 | 4/2/2 | 2 | 31 | 2267 | |
quyuan | 1 | 0/0/0 | 6 | 31 | 1847 | |
Xiaomeng Zhao | 3 | 21/20/1 | 40 | 52 | 1406 | |
icecraft | 2 | 8/7/1 | 3 | 3 | 337 | |
yanqiangmiffy (yanqiangmiffy) | 1 | 2/1/1 | 1 | 9 | 313 | |
yyy | 1 | 7/3/4 | 2 | 21 | 310 | |
Kaiwen Liu (papayalove) | 1 | 6/6/0 | 2 | 7 | 284 | |
sfk | 2 | 3/3/0 | 8 | 2 | 22 | |
Bin Wang | 1 | 0/0/0 | 1 | 3 | 10 | |
github-actions[bot] | 1 | 0/0/0 | 1 | 1 | 8 | |
zhouW (DTwz) | 0 | 1/0/1 | 0 | 0 | 0 | |
Lynn Ly (Ly-Lynn) | 0 | 1/0/1 | 0 | 0 | 0 | |
Lyu Han (lvhan028) | 0 | 1/0/0 | 0 | 0 | 0 | |
Siyu Hao (GDDGCZ518) | 0 | 1/1/0 | 0 | 0 | 0 | |
None (strongerfly) | 0 | 3/0/2 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The recent activity on the MinerU GitHub repository indicates a vibrant engagement with 126 open issues, showcasing a mix of bugs, enhancements, and user inquiries. Notably, several issues highlight recurring problems with PDF parsing, particularly concerning table recognition and OCR capabilities. There is a significant focus on improving the accuracy and efficiency of the extraction process, reflecting user demand for more robust features.
A prominent theme among the issues is the challenge of handling complex document layouts, such as multi-column formats and embedded images. Many users report that tables are often misidentified as images, leading to data loss during parsing. Additionally, there are multiple requests for enhancements related to API functionalities and support for various document formats.
Issue #637: AssertionError due to unsupported UTF-32 encoding in PDF parsing.
Issue #633: Missing content during table recognition.
Issue #627: IndexError encountered when processing PDFs in a multi-threaded environment.
Issue #620: Incompatibility issue with magic-pdf.exe on Windows.
Issue #619: Out of Memory (OOM) error when running multiple commands in CUDA mode.
Issue #618: API call error when uploading the same PDF multiple times in quick succession.
Issue #617: Content loss after updating to version 0.8.x.
Issue #615: Request for support of three-column layout PDF parsing.
This pattern suggests that while the core functionality is appreciated, there is significant room for improvement in terms of robustness and adaptability to various document types.
The ongoing discussions and reported issues reflect a community eager to enhance the capabilities of MinerU. Addressing these concerns will be crucial for maintaining user satisfaction and expanding the tool's applicability across diverse document formats.
The analysis of the pull requests (PRs) for the MinerU project reveals a dynamic and active development environment. The project is focused on enhancing its capabilities in PDF extraction and processing, with significant contributions from various developers. The PRs cover a wide range of improvements, including feature additions, bug fixes, and optimizations.
PR #616: Introduces inference optimization by adding CUDA graph support for the MFR model and provides a multiprocessor demo. This PR is significant as it enhances the performance of the model, making it more efficient.
PR #547: Fixes an issue with filenames containing spaces. While this may seem minor, such fixes are crucial for ensuring smooth operation across different environments.
PR #467: Adds Docker compose file and updates the Dockerfile to use a newer version of MinerU. This makes it easier for users to set up the environment using Docker.
PR #314: Adds support for 'direct_ml' method in PDF extraction kit, expanding the tool's compatibility with different hardware setups.
Closed PRs: A number of PRs have been closed, indicating active maintenance and iterative improvement of the project. For instance, PRs related to fixing bugs (#639, #636) and optimizing existing features (#635) show a commitment to enhancing reliability and performance.
The PRs reflect several key themes in the development of MinerU:
Performance Optimization: Multiple PRs focus on optimizing the performance of various components, such as inference speed and model efficiency. This is crucial for a tool that aims to handle complex document processing tasks quickly and accurately.
Feature Expansion: New features are being added regularly, such as support for additional methods in PDF extraction and enhancements to existing functionalities like Docker support. This indicates a roadmap focused on broadening the tool's capabilities.
Community Contributions: The presence of contributions from various developers suggests an active community around MinerU. This is beneficial for open-source projects as it brings diverse perspectives and expertise into the development process.
Continuous Improvement: The quick turnaround on bug fixes and optimizations shows a strong commitment to maintaining high standards of quality and performance. This is essential for user trust and satisfaction.
In conclusion, MinerU is evolving rapidly with a clear focus on enhancing its core functionalities while ensuring ease of use through better deployment options like Docker. The active involvement of the community in its development is a positive sign for its future growth and improvement.
Xiaomeng Zhao (myhloli)
version.py
with a new version.pdf_extract_kit
to use direct image cropping with layout detection.icecraft
drunkpig
Focusshang
quyuan
LollipopsAndWine (linfeng)
dt-yy
wangbinDL
The development team is actively engaged in improving the MinerU project through bug fixes, feature enhancements, and comprehensive documentation updates. The collaborative nature of the team fosters rapid development cycles, ensuring that user feedback is integrated effectively into ongoing improvements.