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To exit the screen, use CTRL+A D
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1.1 Checking if the batch was completely copied
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Example: MD_2024-07-02
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ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/MD_2024-07-02/*.ARW | wc -l |
output: 560
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ls /home/psa_images/temp_data/semifield-upload/MD_2024-07-02/*.ARW | wc -l |
output (before running the pipeline): 560
output (after running the pipeline): 0
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ls /mnt/research-projects/s/screberg/longterm_images2/semifield-developed-images/MD_2024-07-02/images/*.jpg | wc -l |
output (after running the pipeline): 560
1.12 Trouble shooting:
If developed jpgs are not in the longterm storage, check to see if they’re still in the local temp_data outputs folder:
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When entire batch is fully completed, the row can be hidden by right clicking on the row #, then click hide.
5
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4.1 Installing conda (miniconda)
Use these commands below from the command line in the SUNNY server:
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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:
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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:
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conda activate <your env name>
cd /home/psa_images/analyze_blobs
python ANALYZE_BLOB.py |
Creates 2 time stamped files in the “results” folder in the main project directory.
A text files that provides a general summary of missing batches
A csv file that can be viewed in excel or google docs
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. Common & Useful Commands
Available batches:
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ls /mnt/research-projects/s/screberg/longterm_images2/semifield-upload/ -lh |
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