330 - Fine tuning Detectron2 for instance segmentation using custom data

This video tutorial explains the process of fine tuning Detectron2 for instance segmentation using custom data. It walks you through the entire process, from annotating your data, to training a model, to segmenting images, to measuring object morphological parameters, to exporting individual masks (results) as images for further processing.

Code generated in the video can be downloaded from here: https://github.com/bnsreenu/python_fo...

All other code:
https://github.com/bnsreenu/python_fo...

Detectron2 repo: https://github.com/facebookresearch/d...

Annotations were done using Makesense: https://www.makesense.ai/

Dataset from: https://leapmanlab.github.io/dense-cell/
Direct link to the dataset: https://www.dropbox.com/s/68yclbraqq1...

Data courtesy of:
Guay, M.D., Emam, Z.A.S., Anderson, A.B. et al. ​
Dense cellular segmentation for EM using 2D–3D neural network ensembles. Sci Rep 11, 2561 (2021). ​

Data annotated for 4 classes:
1: Cell
2: Mitochondria​
3: Alpha granule​
4: Canalicular vessel​

• #science_technology
• #microscopy
• #python
• #image_processing