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LibreFOMOl-point
LibreYOLO/LibreFOMOl-point
LibreFOMOl-point is a machine learning model from LibreYOLO. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for libreyolo. The card lists the license as mit.
LibreFOMO size-l point-localizer (224×224 input, 28×28 detection grid), packaged for LibreYOLO.
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Public
Updated Jun 26, 2026
Repo size
308 KB
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.pt308 KB · 99%
At a glance
- Library
- libreyolo
- License
- mit
- Access
- Public
- Created
- Jun 26, 2026
- Updated
- Jun 26, 2026
- SHA
- 688f7414
Model card
From the Hugging Face model README
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
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.
- Library
- libreyolo
- License
- mit
- Created
- Jun 26, 2026
- Updated
- Jun 26, 2026