Field Preprocessing

List of things we want to include

1. Adding steps about the tools and installing those tools ( rawtherapee, mobaxterm)

2. Steps in rawtherapee

3. Command line instructions

4. Pics or screenshots will be very helpful

   1. Provide video overview

5. Requirements

   1. How to get requirements

Backlog Spreadsheet:

1. Download Batch

When downloading a Field batch, we must be navigated to the correct location. We can use tis string of commands:

cd ..
cd psa _images/field_tools/
python3 field_SUNNY_pipeline.py <batch_name>

2. Color Profiling in RawTherapee

Launch RawTherapee:

./RawTherapee_5.8.AppImage

Be sure we are located within the Field_tools folder.

RawTherapee will launch in an separate window and open to the most recent profile that has been worked on. Select the appropriate batch and allow it to load. Scroll through and make a mental note if some images are out of the ordinary (i.e. too bright, too dark, out of focus, etc).

2.1 Look for a Color Checker

We want to use an image with a color checker, if one is available within the batch. Choose the most average looking picture (lighting and color-wise).

In the Field, we typically use a large Color Checker. The Semifield Color Checker may be used instead, but the larger one is preferred for this application.

2.2 Creating a color profile

2.21 Bring in a recent profile

2.22 Color Picker

When making a color profile, we are only interested in using a specific gray with the color picker tool. The gray we want is two squares away from black. Use this gray for every profile you make.

2.23 Adjust exposure & saturation

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2.24 Save new profile and exit RawTherapee

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3. Running the pipeline

When the color profile has been saved, we must send it through the pipeline. Be sure to be navigated to the Field folder and make a new screen, use uppercase r (-R). If returning to an already existing screen, use lowercase r (-r) with the appropriate screen name.

cd ..
cd psa_images/field_tools/
screen -R <batch_name>
python3 field_SUNNY_pipeline.py <batch_name>

To exit the screen, use CTRL+A D

Check on a batch sent into the pipeline by using this string of commands:

cd psa_images/field_tools/
screen -r <batch_name>

If the pipeline has either been completed running or there has been an error running it, there will be an input line. If there is no input line, the process has not completed.

To exit the screen, use CTRL+A D

3.1 Checking the success of the pipeline

If there is an indication the pipeline is finished running, we want to crosscheck the number of images within the original batch with the number of jpgs and pp3s created.

We can use both of these lines respectively:

ls /mnt/research-projects/r/raatwell/longterm_images3/field-batches/<batch>/developed-images/*.jpg | wc -l

ls /mnt/research-projects/r/raatwell/longterm_images3/field-batches/<batch>/developed-images/*.pp3 | wc -l

And compare to number of arws

ls /mnt/research-projects/s/screberg/longterm_images/field-batches/<batch>/*.ARW | wc -l

As long as the output number we get from each of these commands are equivalent, we know we have successfully applied the color profile to every image in the batch.

If the number of jps and pp3s are not equivalent to the original number of images, try running the pipeline again within the screen. Double check the name of the batch that was typed in, this is where errors are likely to happen. Also, be sure to be navigated to the Field folder. If we are within the Semifield folder, the pipeline will run successfully.

Common & Useful Commands

Available batches:

ls /mnt/research-projects/r/raatwell/longterm_images3/field-batches/ -lh

# of arw:

ls /mnt/research-projects/s/screberg/longterm_images/field-batches/<batch>/*.ARW | wc -l

# of pp3 created:

ls /mnt/research-projects/r/raatwell/longterm_images3/field-batches/<batch>/developed-images/*.pp3 | wc -l

# of jpg files processed:

ls /mnt/research-projects/r/raatwell/longterm_images3/field-batches/<batch>/developed-images/*.jpg | wc -l