Improve (and Simplify) Data Capture With Google’s ML Kit
summary
Google ML Kit text recognition runs on-device or via GMS, uses embedded models under 5 MB or downloadable models a few hundred KB, and needs API level 19+. Accuracy needs about 16×16 pixels per character and mid-quality images; a quick sample app (one hour) extracts six blocks, 26 elements and eight lines. Zebra integrates it into DataWedge as a free‑form OCR with a resizable frame, viewfinder, zoom/torch, real‑time recognition, returns a JSON array of elements with block/line IDs and a cropped or full image via intents/broadcasts.
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chapters (7)
- 0:00Introduction and speaker intro
- 1:50What is ML Kit
- 4:00ML Kit text recognition overview
- 11:27Text recognition implementation
- 18:54Zebra’s free-form OCR feature
- 22:28DataWedge integration details
- 30:02Cross-platform Zebra integration
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