I've got some images of cell organelles and I really want to avoid labeling them by hand. The images all look something like the image below. Is there already an existing model specifially for cells? I tried it with existing models like mask_rcnn_coco.h5 or deeplabv3_xception65_ade20k.h5 but as they aren't built for cells the results aren't good.

My code is pretty basic right now:

from pixellib.instance import instance_segmentation

from PIL import Image

    def segmentImage():
        segment_image = instance_segmentation()
        segment_image.segmentImage("cell.jpg", output_image_name="cell_seg.jpg", show_bboxes=True)

Cell example image:

cell organelle example image

Example segmentation result:

enter image description here


I am the creator of PixelLib. PixelLib supports instance segmentation of 80 classes of objects using pre-trained coco model. Cell organelles is not part of the classes supported. The only solution is to train your own custom model. PixelLib supports custom training of a model using your own labelled dataset. Read this article I published on how to train a custom model with PixelLib.

  • $\begingroup$ Wow, what an honor that you personally respond. Thank you very much. I actually already found this article and I wanted to avoid labelling the cells by hand. But I guess it pays off in the long run hopefully. I see a lot of potential in your work for Bioinformatics in general and especially for the project i'm working on now. If done right I'm sure PixelLib can help save us a lot of work :) $\endgroup$ – Cowboy_Patrick Dec 11 '20 at 9:53
  • $\begingroup$ Thank you...... $\endgroup$ – Ayoola Olafenwa Dec 12 '20 at 10:40

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