edgaremy/arthropod-detector
By edgaremy · ↓ 0 · ♥ 0 · Updated 2025-11-14
What's in this repo
This page lists the files in edgaremy/arthropod-detector, including yolo11l_ArthroNat+flatbug.onnx, yolo11l_ArthroNat_mosaic33.onnx, yolo11n_ArthroNat+flatbug.onnx and more.
- 4 ONNX models (.onnx files)
- 10 files, including 4 .onnx, 4 .pt, 1 .md
- Last updated 2025-11-14
ONNX files
| File | Size | Download |
|---|---|---|
| yolo11l_ArthroNat+flatbug.onnx | — | Download |
| yolo11l_ArthroNat_mosaic33.onnx | — | Download |
| yolo11n_ArthroNat+flatbug.onnx | — | Download |
| yolo11n_ArthroNat_mosaic33.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Arthropod Detector 🐞
A YOLO11 detection model trained on images of French Terrestrial Arthropods.
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Dataset Repository: github.com/edgaremy/arthropod-detection-dataset
Associated Paper: To be published
Model Description
- Developed by: Edgar Remy
- Model type: YOLO11 family
- License: MIT
- Finetuned from model: Ultralytics/YOLO11
Get Started with the Model
Use the code below to get started with the model in Python.
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
# Download weights from Hugging Face Hub
weights = hf_hub_download(
repo_id="edgaremy/arthropod-detector",
filename="yolo11l_arthropod_0.413.pt"
)
# Load the model with Ultralytics YOLO
model = YOLO(weights)
Multiple sizes of models are available:
- YOLO11n (nano):
yolo11n_arthropod_0.437.pt - YOLO11l (large):
yolo11l_arthropod_0.413.pt
The 0.437 and 0.413 correspond to their respective optimal confidence threshold, estimated on the validation set.
For more details, check out:
- The dedicated Dataset Repo on GitHub
- Ultralytics Documentation
Metrics
[TODO]
🐞 🐜 🦋 🦗 🐝 🕷️ 🐛 🪰 🪲
Model info
Created: 2025-07-16
Updated: 2025-11-14
View on Hugging FaceFiles (10)
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