Testing labels
Testing labels
What the real-world label corpora measure against Labelary
The suite renders every label in the corpora below on each test run, and compares the output with Labelary's for the same input.
| Corpus | Labels | Pass | Known defect | No comparison | Widest |
|---|---|---|---|---|---|
| Orderful labels | 153 | 153 | 0 | 0 | 4.81% |
| Zebrash reference labels | 46 | 46 | 0 | 0 | 4.71% |
| BinaryKits.Zpl reference labels | 9 | 9 | 0 | 0 | 0.98% |
| zpl-toolchain sample labels | 6 | 6 | 0 | 0 | 3.10% |
| Assorted example labels | 5 | 4 | 0 | 1 | 3.36% |
| Labelize reference labels | 4 | 4 | 0 | 0 | 2.69% |
223 labels across 6 corpora. The status reads off each label's audited record, never off the percentage. pass means the layout and the barcode data match; known defect means the output differs in what it says, whatever the pixel count.