Repository for the semester project carried out by Octavio Profeta in the spring of 2024, under the supervision of Pr. Francesco Mondada and Cyril Monette

hive2_rpi1_240423-034701Z hive2_rpi2_240425-164102Z hive2_rpi3_240423-020502Z hive2_rpi4_240424-014501Z

All the necessary dataset is in the live_bees folder

If you don't have all annotation (live_bees/rpi/masks/.csv):

0. Run the napari_annotation/pipeline.ipynb notebook until the indicated mark to start annotating. You need to do that for each missing RPi's masks
   • Once done with one RPi, run the remaining cells to save the masks
   • Rerun the notebook for each missing RPi's masks

If you have all the masks:

1. Run napari_annotation/csv_to_mask.ipynb notebook for each RPi
2. Run napari_annotation/csv_to_contour.ipynb notebook for each RPi

You can now start to run the mask finding pipelines:

3. Run the aa_thresholding/thresholding.ipynb notebook for each RPi. The resulting masks are in a_processed_images/thresholding folder
4. Run the aa_region_growing/region_growing.ipynb notebook for each RPi. The resulting masks are in a_processed_images/region_growing folder
5. Run the aa_ilastik/ilastik.ipynb notebook for each RPi. The resulting masks are in a_processed_images/ilastik folder
6. Run the aa_optical_flow/optical_flow.ipynb notebook for each RPi. The resulting masks are in a_processed_images/optical_flow folder

Once you have all processed images, run the mask finding pipeline:

7. Run the contour_finding.ipynb notebook notebook for each RPi and each method. The resulting masks are in a_found_masks/method/rpi folder.

   • Note: if you did not uncomment the commented code, you can run the next section

8. You can now run the a_xor_results/xor.ipynb notebook in order to get the XOR masks. The resulting masks are in a_xor_results/method folder.