Model Card for universal-logo-detector
This object detection model was fine-tuned using the Ultralytics YOLO library.
Model Details
Model Description
- Developed by: Open Food Facts
- Model type: object detection
- License: agpl-3.0
- Finetuned from model [optional]: yolov8s.pt
Training Details
Training Data
The model was fine-tuned using the following dataset: openfoodfacts/universal-logo-detector (revision: v1.4).
Training Procedure
Dependency versions:
- ultralytics: 8.3.223
- pytorch: 2.9.0+cu128
Training Hyperparameters
- Epochs: 300
- Batch size: 64
- Image size: 640
Evaluation
The following evaluation metrics were obtained after training the model:
metrics/precision(B): 0.8570181840729786
metrics/recall(B): 0.7192719092719092
metrics/mAP50(B): 0.8371955004759525
metrics/mAP50-95(B): 0.6379071854832687
fitness: 0.6379071854832687
Evaluation on exported models
The model was also evaluated after exporting to ONNX and TensorRT formats. The following metrics were obtained:
ONNX export
metrics/precision(B): 0.8934595473774011
metrics/recall(B): 0.68
metrics/mAP50(B): 0.8107887350032505
metrics/mAP50-95(B): 0.6517839531367096
fitness: 0.6517839531367096
TENSORRT export
metrics/precision(B): 0.893459487354923
metrics/recall(B): 0.68
metrics/mAP50(B): 0.8107887350032505
metrics/mAP50-95(B): 0.6517839531367096
fitness: 0.6517839531367096
Files
Most files stored on the repo are standard files created during training with the Ultralytics YOLO library.
What was added:
- an ONNX export of the trained model (best model), stored in
weights/model.onnx. - a Parquet file containing predictions on the full dataset, stored in
predictions.parquet. - a TensorRT engine export of the trained model, stored in
weights/model.engine. - metrics JSON files for each exported model format, stored in
metrics_*.json:metrics.json: metrics for the original PyTorch modelmetrics_onnx.json: metrics for the ONNX exported modelmetrics_tensorrt.json: metrics for the TensorRT exported model
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