@ -105,7 +105,20 @@ Script Logic: For every site in oneDrive CoastSnap directory, iterate through th
#### Manual tagging
#### Manual tagging
If you want a bit more control over your image tagging, you'll have to do it from the command line. `cd` to this repo and activate the coastsnap conda environment with `activate coastsnap`. Now `cd` to the `CoastsnapAuto/coastsnap` directory. From here, your options are:
If you want a bit more control over your image tagging, you'll have to do it from the command line. `cd` to this repo and activate the coastsnap conda environment with `activate coastsnap`. Now `cd` to the `CoastsnapAuto/coastsnap` directory. From here, your options are:
1.
1. Tag images for a specific site
`python tag_registered.py --site [SITE_NAME]`
2. Tag images that have been reregistered (i.e. Deleted from the Photoshop directory and registered again)
`python tag_registered.py --tag_reregistered`
3. Tag images that have been deleted from the Registered directory
@ -117,7 +130,7 @@ Generates `4_images_snapshot.csv` which contains information about the CoastSnap
site | # processed | # photoshop | # registered | stability | most recently deleted
site | # processed | # photoshop | # registered | stability | most recently deleted
* stability (%) = # registered / # processed. This formula is based on the assumption that someone will manually remove poorly registered images in `Images/Registered`. Thus stability represents the percentage of images that had good registration.
* stability (%) = # registered / # photoshop. This formula is based on the assumption that someone will manually remove poorly registered images in `Images/Registered`. Thus stability represents the percentage of images that had good registration.
* most recently deleted. This is the image date of the most recently deleted in `Images/Registered`. Could be useful to know for manual refining, so the user doesn't have to check every image each time.
* most recently deleted. This is the image date of the most recently deleted in `Images/Registered`. Could be useful to know for manual refining, so the user doesn't have to check every image each time.