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- Demonstration of use of BD Fiddle
- Sign up for Brown Dog Service
- Obtain a key/token using curl or Postman
- Use token and bd fiddle interface to obtain to see BD in action.
- Copy paste the python code snnipet and use it the application to be explained next.
- Create an application/use case using BD services
Possible application applications --- Given a collection of images with text in it (or scanned handwritten documents image), try to search those images based on its content.
- One can upload images from local directory or use flicker API (??) to obtain images
- Write a Python script to upload all images to BD
- Make sure OCR (Census Extractor) is running
- Once technical metadata is obtained from BD, index it tags and technical metadata in an locally running Elasticsearch
- Search for the image using ES query
- Given a collection of text files from a survey or reviews for a book/movie, use sentiment analysis extractor to calculate the sentiment value for each file and group similar values together.
- Write a Python script to upload all files from a directory to the BD API
- Saves the results for each text file in a single file
- Create separate folders and move the file based on the value
- Use Wikipedia API
- Given a collection of images with text in it (or scanned handwritten documents image), try to search those images based on its content.
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