# PADDLEPADDLE/PADDLEOCR SLOC report

> As of 2026-09-16 (commit dab3fe353790), PADDLEPADDLE/PADDLEOCR contains 443,828 total lines: 273,568 code, 145,762 comments, 24,498 blank, across 1,571 files in 29 languages (top: JSON 39.9%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

PADDLEPADDLE/PADDLEOCR has 273,568 source lines of code out of 443,828 total lines across 1,571 files, counted from the dab3fe35379033fdcb2d0e9572fac0b36c9a9ebf ref at commit dab3fe353790 by the OctoCounts tokei engine on 2026-09-16. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving PADDLEPADDLE/PADDLEOCR to commit dab3fe353790, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

## Repository size insights

This is a large codebase by counted code lines. Code represents 61.6% of all lines, comments represent 32.8%, and the repository averages 174 code lines per file. JSON accounts for 39.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| JSON | 28 | 109,162 | 109,162 | 0 | 0 |
| Python | 542 | 116,362 | 94,293 | 8,218 | 13,851 |
| YAML | 226 | 27,533 | 25,794 | 283 | 1,456 |
| C++ | 54 | 20,733 | 16,998 | 1,676 | 2,059 |
| Shell | 49 | 6,969 | 5,880 | 512 | 577 |
| TypeScript | 54 | 6,332 | 5,299 | 357 | 676 |
| Swift | 33 | 5,658 | 4,049 | 992 | 617 |
| Kotlin | 43 | 3,386 | 2,514 | 553 | 319 |
| C Header | 60 | 3,910 | 2,507 | 815 | 588 |
| Go | 14 | 1,916 | 1,537 | 199 | 180 |
| Java | 8 | 1,467 | 1,233 | 58 | 176 |
| Dockerfile | 22 | 1,104 | 819 | 30 | 255 |

Top language (JSON 39.9%). Generated at 2026-09-16T17:58:32.317547282+00:00. Canonical report: https://octocounts.com/github/PADDLEPADDLE/PADDLEOCR

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/PADDLEPADDLE/PADDLEOCR/commit/dab3fe35379033fdcb2d0e9572fac0b36c9a9ebf?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does PADDLEPADDLE/PADDLEOCR have?

PADDLEPADDLE/PADDLEOCR has 443,828 total lines, including 273,568 code lines, 145,762 comment lines, and 24,498 blank lines.

### How was the PADDLEPADDLE/PADDLEOCR line count measured?

OctoCounts resolved the public GitHub repository to commit dab3fe353790, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for PADDLEPADDLE/PADDLEOCR?

This OctoCounts report was generated from dab3fe35379033fdcb2d0e9572fac0b36c9a9ebf at commit dab3fe353790 on 2026-09-16T17:58:32.317547282+00:00.

## Similar repository reports

- [netease-youdao/Confucius4-TTS](https://octocounts.com/github/netease-youdao/Confucius4-TTS) — JSON, 276,249 code lines
- [searxng/searxng](https://octocounts.com/github/searxng/searxng) — JSON, 268,461 code lines
- [polymorph-components/polymorph-webcrypto](https://octocounts.com/github/polymorph-components/polymorph-webcrypto) — JSON, 262,428 code lines
- [usekaneo/kaneo](https://octocounts.com/github/usekaneo/kaneo) — JSON, 301,993 code lines
- [google-deepmind/weathernext](https://octocounts.com/github/google-deepmind/weathernext) — JSON, 302,272 code lines
- [containers/kubernetes-mcp-server](https://octocounts.com/github/containers/kubernetes-mcp-server) — JSON, 243,779 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)
