Inspiration
We wanted to make historical data easily accessible to others. While it may take ages to flip through a 1995 Sears shopping catalog, it takes practically no time at all to make a simple keyword search on Cataloger.
What it does
Catalog stores old catalog data and allows for quick lookup of the average cost of an item (e.g. a dress), all the while accounting for inflation and conversion into other currencies.
How we built it
We used the Google Cloud Vision API to scan a 600-page JC Penney shopping catalog from 1996, using regex to determine the prices and relevant keywords of items. We then used the XE Currency Data API to get historical and present exchange rates for other currencies.
Challenges we ran into
Finding a catalog with a consistent layout was rather difficult. It was also an issue trying to isolate items from one another, since the OCR tended to produce blocks of text and couldn't easily discern between paragraphs.
Accomplishments that we're proud of
We're proud of that fact that we managed to complete a working product by the deadline.
What we learned
We learned how to use the Google Cloud Vision API to parse text from images and basic functionalities of the XE Currency Data API.
What's next for Cataloger
Next steps would include enlarging the selection of products that can be searched for, as well as getting prices from different years, which would allow for analysis of trends of items' values changing over time.
Built With
- google-cloud-vision-api
- javascript
- json
- python
- xe-currency-data-api
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