4 posts tagged with "OCR"

I diffed the EasyOCR and Qwen3-VL transcriptions of 444 Soviet cookbook pages against each other, and the two engines produced character-for-character identical text on only 5 pages. All 5 are nearly blank (a heading or a page number, 13 to 24 characters each). The plan from the previous post was to treat pages where both engines agree as "probably accurate" and hand-check only the rest. On real content pages that agreement almost never happens, so cross-engine agreement doesn't work as the cheap accuracy filter I hoped for.

Docling's vision-language model pipeline, running the 4B-parameter Qwen3-VL model locally, processed 444 cookbook page images for the soviet.recipes project at a 99.5% success rate. Compared to the earlier EasyOCR run, it gave up every piece of debugging output that run had: no text-region overlays, no per-page confidence score, no reading-order artifacts. It also ran far slower, and Docling still processes one-page image documents one at a time, so the batch took about 26.3 hours.

Docling with the EasyOCR engine extracted the Cyrillic text and page structure from a scanned Soviet cookbook, but it dropped text where the pages curved away from the camera. That data loss makes this configuration insufficient on its own for the soviet.recipes project. I tested four sample pages configured for Russian and English, using Kiro.dev to write the script.

Phase 1 of the soviet.recipes project is done: every page of the cookbook is now captured as a set of 224 high-resolution DSLR images. Now I'm planning how to turn those images into machine-readable text.