If Squid software (https://github.com/Cephla-Lab/Squid) is not installed, run the following commands before continue to the next steps:
wget https://raw.githubusercontent.com/hongquanli/octopi-research/master/software/setup_22.04.sh
chmod +x setup_22.04.sh
./setup_22.04.shIf Squid software is already installed, start from here:
pip install dask_image
pip install ome_zarr
pip install aicsimageio
pip install basicpyClone this repo. In terminal change to its directory and run the following command:
For graphical user interface:
python3 stitcher_gui.pyFor command line usage:
python3 stitcher_cli.py -i /path/to/imagesor with registration and flatfield correction
python stitcher_cli.py -i /path/to/images -r -ff --registration-channel "Fluorescence 488 nm Ex"- The input folder should be the folder named with Experiment ID which contains all the timepoints of your acquired images,
acquisition parameters.jsonandconfigurations.xml - Make sure
acquisiton parameters.jsonfile contains the correct information for objective magnification and sensor_pixel_size_um, etc. - The stitcher works with imaging data acquired with the latest Squid software. For data acquired with older version software, use
update_coordinates.pyto updatecoordinates.csvformat. See Updating coordinates.csv file part.
- When this option is checked, the stitcher will apply flatfield to individual images using baSiCPy when stitching
- When this option is checked, Cross-Correlation Registration will be performed. Otherwise the images will be stitched based on their coordinates in
coordinates.csvfile
- Being implemented. Not ready yet.
- Either OME-ZARR or OME-TIFF
- Opens filepath to visualize in napari viewer
Run:
python3 update_coordinates.py <input folder>- This script updates
coordinates.csvin data acquired with older version Squid software to match the format in latest version - The input folder should be the folder named with Experiment ID which contains all the timepoints of your acquired images,
acquisition parameters.jsonandconfigurations.xml - Only works for data acquired with Wellplate Multipoint
Use convert_to_coordinate_acquisition.py. To be tested.