Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-title: Dummy Opf 2
+title: OPF Image Anonymizer
 emoji: 🦀
 colorFrom: yellow
 colorTo: pink
@@ -8,7 +8,40 @@ sdk_version: 6.13.0
 app_file: app_v2.py
 pinned: false
 license: apache-2.0
-short_description: dummy opf demo
+short_description: Use OAI's Privacy Filter to redact PII info from any image
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Image Anonymizer
+
+Drop in a screenshot of a chat, email, or document or any image for that matter. The app runs OCR, feeds the recognised text through **OpenAI Privacy Filter**, maps detected PII spans back to their original pixel positions, and overlays black bars in a canvas editor. Toggle, move, add or delete bars — then save a ready-for-Twitter PNG or copy it straight to the clipboard.
+
+## Features
+
+- **OCR + privacy filter in one pass**: Tesseract extracts word-level boxes, the filter model finds PII char spans, the backend unions the two into redaction rectangles.
+- **Canvas editor**: not expressible with `gr.Blocks` but possible with `gr.Server`. Drag to draw bars, click to select, drag to move, Delete to remove. Paste from clipboard to upload.
+- **Eight PII categories**: Person, Address, Email, Phone, URL, Date, Account Number, Secret — each toggleable from the sidebar.
+- **Export locally**: download as PNG or copy to clipboard. No upload of edits, no server round-trip.
+
+## Architecture
+
+- **Backend**: `gr.Server` — FastAPI route `POST /api/detect` accepts an image, runs OCR + the filter on GPU, returns the PNG as a base64 data URL plus a list of pixel boxes. Also exposes a `anonymize_screenshot` Gradio API.
+- **Frontend**: custom HTML/CSS/JS served from the same server. Uses `<canvas>` at natural image resolution (scaled for display); final export is rendered to an offscreen canvas at full resolution.
+- **Model**: `charles-first-org/second-model` loaded with the same hand-rolled inference path used in the sibling `PII Reveal` Space.
+
+## How it works
+
+1. User drops a screenshot (PNG/JPG/WebP) or pastes from clipboard.
+2. `pytesseract.image_to_data` returns per-word text + bounding boxes. We reconstruct the full text with line breaks, keeping a char-offset → box map.
+3. The full text is passed through the privacy filter (single forward pass, 128k context).
+4. Detected char spans are looked up against the word map; overlapping words are grouped by line and unioned into rectangles with a small padding.
+5. The frontend renders the image and boxes on a canvas. User edits locally and exports.
+
+## API
+
+```python
+from gradio_client import Client, file
+client = Client("YOUR_SPACE_ID")
+result = client.predict(file("screenshot.png"), api_name="/anonymize_screenshot")
+# -> {"width": ..., "height": ..., "boxes": [{"x","y","w","h","label","text"}, ...], ...}
+```