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LibreYOLO/
LibreFOMOl-point

Name: LibreFOMOl-point
Availability: InStock

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LibreFOMOl-point

LibreFOMO size-l point-localizer (224×224 input, 28×28 detection grid), packaged for LibreYOLO.

Architecture-only weights. These weights are randomly initialised (nc=1, class "object"). They produce no meaningful predictions out of the box. Fine-tune on your own labelled data before deploying. See the LibreYOLO training guide for instructions.

Architecture

LibreFOMO is a MobileNetV2-derived point-localizer designed for counting and locating objects at very low resolutions. It outputs a spatial grid of per-class confidence scores rather than bounding boxes, making it well-suited for fixed-camera occupancy monitoring and object counting on edge devices.

Size	Input	Grid	Parameters
l	224×224	28×28	~297 KB

Usage

python

from libreyolo import LibreFOMO

# Load architecture weights (random init — fine-tune before use)
model = LibreFOMO("LibreFOMOl-point.pt")

# Fine-tune on your data
model.train(data="your_data.yaml", allow_experimental=True)

License

MIT License. See the LICENSE file in this repository.

LibreYOLO/LibreFOMOl-point

LibreFOMOl-point

Architecture

Usage

License

LibreYOLO/
LibreFOMOl-point