OCR for daily travel expense report generation

• there are two scripts

  • process_handler_00_rename_files.py: image file renamer

    • renames the image file according to the date, time-of-day and fare in the image

  • process_handler_01_create_csv.py: image file name to csv

    • extracts the information in the file names into a csv

• after running the first script, ensure image file names do not have <---> in their file names, by filling in the appropriate details

• after running the second script, open the .csv. file output at the end of it, and sort by the first column

  • rearrange the night and morning columns as necessary to match the final document

step 1

• collect all the screenshots from OLA App > My Rides for the month in a directory within the root directory
• name the directory containing the images in the following pattern
  • images-[month-name]-[year]
  • this name will be used in step 2 and step 4

step 2

• in file process_handler_00_rename_files.py, set the image_dir variable to the above directory name

• run python process_handler_00_rename_files.py

• this will rename the image files with the date, day, time-of-day and fare in the filename

• zip this folder and put it up on google drive

step 3

• manual cleanup

  • not all files will be renamed correctly

• file names that need attention will have <---> in the file name

  • open the image file and rename it with the correct details by observing the details from the image

step 4

• in file process_handler_01_create_csv.py, set the image_dir variable to the same above directory name

• run python process_handler_01_create_csv.py

• open the .csv file generated using a spreadsheet editor and sort the sheet by the first column, which has the date and day

  • rearrange the night and morning columns to match the final report template

Troubleshooting

• pip install -r requirements.txt

  • installs the requirements in the virtual environment

• if this install fails with Errno 13:

  • delete the bin and the lib folder and recreate a virtual environment
  • then run pip install -r requirements.txt

• if it still complains, upgrade pip and then install from requirements

  • pip install --upgrade pip