README.md

---
license: afl-3.0
task_categories:
- object-detection
language:
- en
---

# Annotation
Each date in the Products-Real and Products-Synth datasets is annotated with class, bounding box coordinates, date transcription, image width, and height. There are four classes defined: date, due, prod, and code in the training sets. Expiration dates in the test set of Product-Real are specifically labeled as "exp" class for easy evaluation, unlike the training set of Product-Real. Each component in the Date-Real and Date-Synth datasets is annotated with class, bounding box, and transcription. The day, month, and year are used as the classes for each component of the dates. Moreover, Components-Real and Components-Synth datasets consist of the components of the day, month, and year and their transcriptions.

# Citation

Dataset published originally in `A Generalized Framework for Recognition of Expiration Date on Product Packages Using Fully Convolutional Networks`
@article{seker2022generalized,
    title={A generalized framework for recognition of expiration dates on product packages using fully convolutional networks},
    author={Seker, Ahmet Cagatay and Ahn, Sang Chul},
    journal={Expert Systems with Applications},
    pages={117310},
    year={2022},
    publisher={Elsevier}
  }