Collections-OCR/README.md

Collections-OCR

A few scripts that batches of collections label-images through OCR

Google Cloud Vision API & ocrCloudVision.R

Dependencies

Make sure to install these libraries first:

• googleCloudVisionR - to do OCR magic
• Other dependencies include readr, tidyr, stringr for data handling

How to run ocrCloudVision.R:

Notes:

• This currently uses Google's Cloud Vision API, which requires:
  • Being aware of pricing & quotas for the Google Vision API
  • Setting up a project on Google Cloud Platform
  • Authenticating your magine by setting up a Service account & key
    • Get help from the cloudyr repo for googleCloudVisionR
• This can takes over 30 seconds per label-image.
  • Be mindful how many images you add to your "images" directory.
  • Be mindful of your internet connection speed
  • Keep image sizes under 20MB (Overall, smaller image files transfer and process more quickly)
• Output likely needs some [or many] follow-up/clean-up steps.
  • Batch similar images together to streamline follow-up steps.

To run the script:

1. Add a folder named "images" to this script's directory
2. Add the images (JPG & JPEG) you'd like to OCR to that directory
3. Run the script (Rscript ocrCloudVision.R)

Output from ocrCloudVision.R:

A CSV named "ocrText-[Date-time].csv", containing these columns:

• "image" = filename for each JPG and JPEG
• "imagesize" = filesize for each image (in MB)
• "ocr_start" = start-date and time when an image was submitted to the Google Vision API
• "ocr_duration" = duration (in seconds) of the OCR process
• "line_count" = number of lines in each OCR transcription
• "Line1" - "Line[N]" = text for each line in the OCR transcription of an image.
  • the number of "Line" columns will match the maximum number of lines as needed.

Tesseract & ocrMangle.R

Dependencies

Make sure to install these libraries first:

• magick - to read in image files
• tesseract - to do OCR magic
• stringr - to split the OCR'ed lines to columns

How to run ocrMangle.R:

Notes:

• This can takes over 10 seconds per label-image.
  • Be mindful how many images you add to your "images" directory.
• This currently uses Tesseract's English ("eng"), German ("deu"), and Latin ("lat") libraries.
• Output likely needs some [or many] follow-up/clean-up steps.
  • Batch similar images together to streamline follow-up steps.

To run the script:

1. Add a folder named "images" to this script's directory
2. Add the images (JPG & JPEG) you'd like to OCR to that directory
3. Run the script (Rscript ocrMangle.R)

Output from ocrMangle.R:

A CSV named "ocrText-[Date-time].csv", containing these columns:

• "image" = filename for each JPG and JPEG
• "line_count" = number of lines in each OCR transcription
• "Line1" - "Line[N]" = text for each line in the OCR transcription.
  • the number of "Line" columns will match the maximum number of lines as needed.

Google Drive API & ocrGoogleDrive.R

This is drafty; might work for small batches, but needs work.