# tesseract-ocr/tesseract > Open-source OCR engine libtesseract and CLI tool tesseract for recognizing text in images. Supports 100+ languages, PNG/JPEG/TIFF input, and output in text, hOCR, PDF, TSV, ALTO. - Magnitude: 2.1 out of 10 — Steady - Stars: 77,313 total · +11 stars measured 2026-11-03, 00:36–13:55 UTC, ≈ 19 by evening - Star trust: star growth looks organic - Category: Language models · Language: C++ · License: Apache-2.0 · Created: 2014-08-12 · Last push: 2026-11-02 - GitHub: https://github.com/tesseract-ocr/tesseract · Homepage: https://tesseract-ocr.github.io/ · Page: https://gitnova.dev/en/r/tesseract-ocr/tesseract ## Useful for - Convert a scanned document into a searchable PDF with a text layer - Extract text from screenshots or photos in one of 100+ languages - Embed libtesseract into your app via the C/C++ API or language wrappers ## Why it’s here - Star-counter measurements on 2026-11-03 (UTC), 00:36–13:55: 77302 → 77313 stars (+11). This is the change over that interval. - Estimated end-of-day forecast: about +19 stars, using observed gains and the previous day. - About 8 forks a day — people are taking the code. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 10,899 - Issues and pull requests: 4,595 - Watchers: 1,709 - Average over the last week: 20 per day - Usual pace: 19 per day - Stars in the last hour (measured): 0 - Latest release: 5.5.4 (2026-10-28) ## Stars per day, last 30 days (oldest → newest, today is partial) 2026-10-05 … 2026-11-03: 17, 14, 20, 28, 10, 13, 21, 39, 28, 22, 25, 11, 18, 20, 10, 23, 17, 19, 22, 18, 15, 19, 29, 21, 16, 25, 23, 21, 18, 11 ## Magnitude by day, last 14 days 09-28 1.9, 09-29 2.0, 09-30 1.9, 10-01 1.7, 10-02 1.8, 10-03 1.7, 10-04 1.4, 10-28 2.0, 10-29 2.1, 10-30 2.1, 10-31 2.2, 11-01 2.2, 11-02 2.2, 11-03 2.2 ## More in this category 1. **NVIDIA/auto-ontology** — 8.8 · Breakout · Language models · Python · +1,111 stars measured 2026-11-03, 00:35–13:47 UTC, ≈ 1,637 by evening NVIDIA's Python framework that builds a semantic ontology graph over enterprise metadata, giving LLM agents trusted metric and entity definitions for reliable text-to-SQL. Full card: https://gitnova.dev/en/r/NVIDIA/auto-ontology.md 2. **karpathy/nanochat** — 7.2 · Breakout · Language models · Python · +265 stars measured 2026-11-03, 00:30–13:47 UTC, ≈ 462 by evening A minimal experimental harness for training LLMs on a single GPU node, covering tokenization, pretraining, finetuning, evaluation and inference. It lets you train a GPT-2-capability model for about $48 and chat with it via CLI. Full card: https://gitnova.dev/en/r/karpathy/nanochat.md 3. **p-e-w/heretic** — 6.3 · Breakout · Language models · Python · +415 stars measured 2026-11-03, 00:31–13:47 UTC, ≈ 694 by evening A tool for fully automatic removal of censorship (safety alignment) from transformer-based language models using directional ablation and Optuna-based parameter optimization. Full card: https://gitnova.dev/en/r/p-e-w/heretic.md 4. **FlashML-org/FreeToken** — 6.0 · Breakout · Language models · Python · +374 stars measured 2026-11-03, 00:31–13:47 UTC, ≈ 647 by evening A Mixture-of-Experts inference engine for running frontier-scale open-weight MoE models (290B+) on consumer hardware — GPUs, CPUs, and host memory. Aimed at users who want to run frontier models locally. Full card: https://gitnova.dev/en/r/FlashML-org/FreeToken.md 5. **FareedKhan-dev/kimi-k3-in-c** — 5.7 · Breakout · Language models · C · +214 stars measured 2026-11-03, 00:32–13:47 UTC, ≈ 348 by evening A portable C99 inference engine that runs the 2.78-trillion-parameter Kimi K3 model on a single CPU within 8.24 GB of RAM, with no BLAS, framework, or GPU. The model streams from disk, and memory only affects speed. Full card: https://gitnova.dev/en/r/FareedKhan-dev/kimi-k3-in-c.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-11-03 14:05 UTC, updated every 30 minutes.