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OCR + NER in the browser — your data never leaves your device.","maintainers":[{"name":"athal7","email":"athal7@me.com"}],"readme":"# image-pii-redactor\n\n[![npm version](https://img.shields.io/npm/v/image-pii-redactor)](https://www.npmjs.com/package/image-pii-redactor)\n\nA Web Component that redacts personal information from AI chat screenshots entirely in the browser. No data ever leaves your device.\n\n**[Try the live demo →](https://athal7.github.io/image-pii-redactor/)**\n\n```html\n<pii-redactor></pii-redactor>\n```\n\nUpload a screenshot → PII is detected and highlighted → review and adjust → export a redacted PNG.\n\n## How it works\n\n1. **OCR** — [Tesseract.js](https://github.com/naptha/tesseract.js) extracts text and word-level bounding boxes from the image\n2. **PII detection** — A multilingual NER model ([`onnx-community/multilang-pii-ner-ONNX`](https://huggingface.co/onnx-community/multilang-pii-ner-ONNX)) via [Transformers.js](https://github.com/xenova/transformers.js) identifies names, addresses, phone numbers, etc. Regex patterns cover structured PII (SSN, credit card, email, IP address) as a fallback\n3. **Review** — An SVG overlay lets you toggle, add, or remove redaction boxes before exporting\n4. **Export** — The final redacted PNG is rendered on a Canvas and returned as a `Blob`\n\nEverything runs in the browser. The OCR engine, NER model, and image processing use WebAssembly and WebGPU — no server, no API call, no telemetry.\n\n## Install\n\n```sh\nnpm install image-pii-redactor\n```\n\n## Usage\n\n### As a Web Component\n\n```html\n<script type=\"module\">\n  import 'image-pii-redactor';\n</script>\n\n<pii-redactor></pii-redactor>\n```\n\nThe component self-registers as `<pii-redactor>`. Drop it anywhere — it works in plain HTML, React, Vue, Svelte, or any framework.\n\n### Listening for the result\n\n```js\nconst redactor = document.querySelector('pii-redactor');\n\nredactor.addEventListener('redaction-complete', (e) => {\n  const { blob, entities, width, height, redactedText } = e.detail;\n  // blob:         PNG Blob with redactions burned in\n  // entities:     array of { label, bbox, source } — no PII, just metadata\n  // redactedText: OCR transcript with redacted words replaced by [REDACTED]\n});\n\nredactor.addEventListener('redaction-cancel', () => {\n  console.log('User cancelled');\n});\n```\n\n### Configuration\n\n```html\n<pii-redactor\n  lang=\"eng\"\n  min-confidence=\"0.7\"\n  use-regex=\"true\"\n  max-file-size=\"20971520\"\n></pii-redactor>\n```\n\nOr via JavaScript:\n\n```js\nredactor.config = {\n  lang: 'eng',                                          // Tesseract language code\n  nerModel: 'onnx-community/multilang-pii-ner-ONNX',   // HuggingFace model ID\n  minConfidence: 0.7,                                   // NER confidence threshold\n  useRegex: true,                                       // also run regex patterns\n  maxFileSize: 20 * 1024 * 1024,                        // 20 MB\n  memoryMode: 'auto',                                   // 'auto' | 'low' | 'normal'\n};\n```\n\n`memoryMode: 'auto'` detects `navigator.deviceMemory` and uses sequential model loading (OCR → terminate → NER) on devices with less than 4 GB RAM.\n\n### Programmatic pipeline\n\nUse the pipeline directly without the UI component:\n\n```js\nimport { analyzeImage, renderRedactedImage, buildRedactedText } from 'image-pii-redactor';\n\nconst result = await analyzeImage(imageBlob, {\n  lang: 'eng',\n  nerModel: 'onnx-community/multilang-pii-ner-ONNX',\n  minConfidence: 0.7,\n}, (progress) => console.log(progress.message));\n\n// result.ocr        — full OCR text + word bboxes\n// result.entities   — detected PII entities with char offsets\n// result.redactions — proposed redaction boxes in pixel coords\n\nconst { blob } = await renderRedactedImage(imageBlob, result.redactions);\nconst redactedText = buildRedactedText(result.ocr, result.redactions, result.entities);\n// redactedText: \"Hello [REDACTED] — thanks for your message\"\n```\n\n### Service Worker (offline + privacy firewall)\n\nAfter the first load, the component works fully offline. Register the included Service Worker to cache model files and optionally block all outbound network requests:\n\n1. Copy `node_modules/image-pii-redactor/public/pii-redactor-sw.js` to your web root\n2. Register it on page load:\n\n```js\nimport { registerServiceWorker } from 'image-pii-redactor';\n\nawait registerServiceWorker();\n```\n\nOnce registered, the SW intercepts HuggingFace model downloads and caches them. After models are warm, you can enable the network firewall to block all external requests — verifiable proof that no image data leaves the browser:\n\n```js\nnavigator.serviceWorker.controller.postMessage({ type: 'ENABLE_FIREWALL' });\n```\n\n## Privacy model\n\n- **All processing is local.** OCR, NER inference, and image rendering run entirely in the browser using WebAssembly (WASM) and optionally WebGPU.\n- **Models are cached after the first download.** Transformers.js and Tesseract.js both use the browser's Cache API and IndexedDB. Subsequent runs are instant and offline.\n- **Airplane mode works.** After the first run, disconnect from the internet and reload — the tool continues to function. This is the user-facing proof that nothing is server-dependent.\n- **The Service Worker provides a hard network fence.** When enabled, the SW blocks all non-cached outbound requests at the browser level, making it impossible for image data to be exfiltrated even by a compromised dependency.\n\n## Browser support\n\n| Feature | Requirement |\n|---------|------------|\n| OCR (Tesseract.js WASM) | Chrome 89+, Firefox 89+, Safari 15+ |\n| NER (Transformers.js WASM) | Same as above |\n| NER (WebGPU acceleration) | Chrome 113+, Edge 113+ |\n| OffscreenCanvas (image pre-processing) | Chrome 69+, Firefox 105+ |\n| Web Components | All modern browsers |\n\nSafari is supported but WebGPU acceleration is not available — inference falls back to WASM automatically.\n\n## Development\n\n```sh\ngit clone https://github.com/athal7/image-pii-redactor\ncd image-pii-redactor\nnpm install\n\nnpm run dev          # start demo at http://localhost:5173\nnpm test             # unit tests (Vitest, ~250ms)\nnpm run test:e2e:fast  # fast e2e tests, no model download needed\nnpm run build        # production library build\n```\n\nE2e tests that exercise the full model pipeline require the dev server to be running:\n\n```sh\nnpm run dev &\nnpm run test:e2e\n```\n\n## License\n\n[MPL-2.0](LICENSE) — Mozilla Public License 2.0. Modifications to library files must be published under the same license; combining with proprietary code in a larger work is permitted.\n","readmeFilename":"README.md"}