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  "title": "textsnap",
  "description": "textsnap converts any image, screenshot, or webpage into plaintext locally via OCR, running fully offline after the first model download. Open source: yes (MIT project; models Apache-2.0); self-hostable (pip install, ONNX runtime, no GPU, no cloud, no API keys). Free; ~186 stars; maker kouhxp.",
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  "one_liner": "textsnap turns any image, screenshot or webpage into plaintext on-device via ONNX OCR, running fully offline after one model download — no GPU or API keys.",
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  "who_its_for": "A builder feeding text into an agent or document pipeline who needs OCR that runs entirely on-device — no cloud OCR API, no GPU, no keys — so image, screenshot, and webpage content becomes plaintext without data leaving the machine.",
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    "note": "MIT for the project, Apache-2.0 for the models, per repo; ~186 stars. Converts any image/screenshot/webpage into plaintext via OCR. Self-hostable: `pip install`, ONNX runtime, no GPU, no cloud, no API keys, fully offline after the first model download (kouhxp/textsnap, verified 2026-09-29)."
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  "caveats": "Verified from the primary repo (2026-09-29); no independent accuracy testing here. OCR quality on low-resolution, skewed, handwritten, or dense-layout inputs is not benchmarked here — evaluate on your own documents. Dual license: MIT for the project, Apache-2.0 for the bundled models. It downloads the model on first run, so the very first use requires network access even though later use is offline.",
  "lead": "textsnap converts any image, screenshot, or webpage into plaintext locally via OCR, and after the first model download it runs fully offline. Open source: yes (MIT for the project; the models are Apache-2.0); self-hostable with a `pip install` on the ONNX runtime — no GPU, no cloud, and no API…",
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      "text": "textsnap converts any image, screenshot, or webpage into plaintext locally via OCR, and after the first model download it runs fully offline. Open source: yes (MIT for the project; the models are Apache-2.0); self-hostable with a `pip install` on the ONNX runtime — no GPU, no cloud, and no API keys. It is free, has ~186 stars, and is maintained by kouhxp."
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      "text": "and after the first model download it runs fully offline. Open source: yes (MIT for the project; the models are Apache-2.0); self-hostable with a `pip install` on the ONNX runtime — no GPU, no cloud, and no API keys. It is free, has ~186 stars, and is maintained by kouhxp.\n\ntextsnap is an on-device OCR primitive aimed at builders who need to turn visual content into text without calling a cloud OCR service. You point it at an image, a screenshot, or a webpage and it returns plaintext, running the model through the ONNX runtime on the local CPU — no GPU required and no API keys to manage. After the initial model download it works entirely offline, so nothing you OCR ever leaves the machine. It installs with `pip`, which makes it easy to drop into an agent or document-ingestion pipeline as the step that feeds text downstream. Open source: yes (MIT project; Apache-2.0 models); self-hostable; free."
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      "text": "manage. After the initial model download it works entirely offline, so nothing you OCR ever leaves the machine. It installs with `pip`, which makes it easy to drop into an agent or document-ingestion pipeline as the step that feeds text downstream. Open source: yes (MIT project; Apache-2.0 models); self-hostable; free.\n\n- MIT for the project, Apache-2.0 for the models, per repo; ~186 stars.\n- Converts any image/screenshot/webpage into plaintext via OCR.\n- Self-hostable: `pip install`, ONNX runtime, no GPU, no cloud, no API keys; fully offline after the first model download (kouhxp/textsnap, verified 2026-09-29).\n- Surfaced via the GTM Stacker studio daily pull (2026-09-29 pass); license/facts verified against the primary repo 2026-09-29."
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      "text": "stars. - Converts any image/screenshot/webpage into plaintext via OCR. - Self-hostable: `pip install`, ONNX runtime, no GPU, no cloud, no API keys; fully offline after the first model download (kouhxp/textsnap, verified 2026-09-29). - Surfaced via the GTM Stacker studio daily pull (2026-09-29 pass); license/facts verified against the primary repo 2026-09-29.\n\nGTM pipelines constantly hit text that is trapped in images — a screenshot of a pricing page, a scanned contract, a chart in a deck, a competitor's site rendered as an image. textsnap turns that into plaintext an agent can read, and it does it locally, which matters when the source contains confidential prospect or deal information you would rather not send to a third-party OCR API. The honest read: OCR accuracy on messy real-world inputs — skew, low resolution, dense tables, handwriting — is not benchmarked here, so test it on your actual documents; and while it runs offline afterward, the first run needs network access to fetch the model."
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