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christiankhoury05/scaplen-lab-drosophila-segmentation
scaplen-lab-drosophila-segmentation is a object detection model from christiankhoury05. Use it when you need objects located in an image. It is set up for ultralytics.
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From the Hugging Face model README

Example output on a real frame: raw footage, then stage 1 whole-fly segmentation, then stage 2 body parts (blue = head, green = thorax, red = abdomen).
Two YOLO26m instance-segmentation models for tracking Drosophila
stage1_wholefly_seg.pt: whole-fly segmentation, one class (fly). Finds and segments every fly in the full frame.stage2_bodyparts_seg.pt: body-part segmentation (head, thorax, abdomen), run on single-fly crops taken from stage 1.Both are YOLO26m (medium). Validation mask mAP@50 is about 0.995 for each.
from ultralytics import YOLO
model = YOLO("stage1_wholefly_seg.pt")
results = model.predict("frame.png")
Full pipeline, training scripts, datasets, and analysis code are on GitHub: https://github.com/ciij05/scaplen-lab
Built by Christian Khoury, Scaplen Lab, 2026.