SemiField Preprocessing

TODOs

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

6. Additional requirements and instructions

   1. Azure Matt

   2. SUNNY Matt

   3. NFS Locker Access Chris?

Backlog Spreadsheet:

1. Download Batch

When downloading a Semifield batch, we need to copy it over to the local user from the NFS Lockers.

cd ..
cd psa_images/semifield_tools/
screen -R <batch_name>
python3 copy_from_lockers.py <batch_name>

Semifield batches can take anywhere from a few minutes to half an hour to copy over, depending on the batch size. This is why it is important to open a new screen for copying. Be sure only to copy one or two batches at a time within their respective screens to avoid disk space problems.

To exit the screen, use CTRL+A D

Checking in to see if the copying of a batch has been completed by using this string of commands:

cd psa_images/semifield_tools/
screen -r <batch_name>

If the batch has either been completed copying or there has been an error copying, 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

1.1 Checking if the batch was completely copied

It is important to check if the copied batch was brought to the local user entirely.

We must know the number of images in the original batch. This can be checked using this command line:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/<batch>/*.ARW | wc -l

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2. Color Profiling in RawTherapee

Launch RawTherapee:

./RawTherapee_5.8.AppImage

Be sure we are located within the Semifield_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 Semifield, we typically use a more compact Color Checker. The Field color checker may be used instead, but the compact one is preferred for this application.

2.2 Creating a color profile

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2.21 Bring in a recent profile

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2.22 Color Picker

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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 Semifield 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/semifield_tools/
screen -R <batch_name>
python3 semifield_CLOUDY_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/semifield_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/s/screberg/longterm_images2/semifield-developed-images/<batch>/images/*.jpg | wc -l

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-developed-images/<batch>/images/*.pp3 | wc -l

And compare to the number of arws using this:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/<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 Semifield folder. If we are within the Field folder, the pipeline will not be successful.

5. Update Backlog Spreadsheet

Change the progress column to the appropriate term to indicate where that batch is in the process. Make any notes/check box when done, if applicable.

When entire batch is fully completed, the row can be hidden by right clicking on the row number, then click hide.

4. Blob Analyzer (????)

4.1 Installing conda (miniconda) 

Use these commands below from the command line in the SUNNY server:

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm  ~/miniconda3/miniconda.sh
~/miniconda3/bin/conda init bash

Close the remote connection, then SSH back in

4.2 Setting up a conda environment

Still in the command line inside of SUNNY:

conda create -n <your env name> python=3.10
conda activate <your env name>
cd /home/psa_images/analyze_blobs
pip install -r requirements.txt

4.3 Running the code 

Your conda environment must be activated to run the code.

Run these in the command line:

conda activate <your env name>
cd /home/psa_images/analyze_blobs
python ANALYZE_BLOB.py

1. Creates 2 time stamped files in the “results” folder in the main project directory. 

   1. A text files that provides a general summary of missing batches

   2. A csv file that can be viewed in excel or google docs

5. Common & Useful Commands

Available batches:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/ -lh

# of images in batch:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/<batch>/*.ARW | wc -l

# of jpgs processed:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-developed-images/<batch>/images/*.jpg | wc -l

# of pp3 files created:

ls /mnt/research-projects/s/screberg/longterm_images2/semifield-developed-images/<batch>/images/*.pp3 | wc -l