metadata
license: mit
datasets:
- ecopus/sign_identification
Model Card for Model ID
This model is an image classifier that identifies images of stop signs. It is trained with Autogluon multimodal on the ecopus/sign_identification dataset.
Model Details
Model Description
This model is an image classifier that identifies images of stop signs. It is trained with Autogluon multimodal on the ecopus/sign_identification dataset.
- Developed by: Sam Der
- Model type: AutoML (AutoGluon MultiModalPredictor with ResNet18 backbone)
- License: MIT
Uses
Direct Use
This model is intended to be used to distinguish stop signs from other street signs.
Training Details
Training Data
- dataset: ecopus/sign_identification
- splits:
- original: 30 original images
- augmented: 385 synthetic images
Training Procedure
- library: AutoGluon MultiModal
- presets: "medium_quality"
- backbone: timm_image → resnet18
Training Hyperparameters
- presets="medium_quality"
- hyperparameters={ "model.names": ["timm_image"], "model.timm_image.checkpoint_name": "resnet18", }
Evaluation
Testing Data, Factors & Metrics
Testing Data
ecopus/sign_identification
Metrics
- accuracy: fraction of correctly predicted labels
- F1 (weighted): harmonic mean of precision and recall, weighted by class support
Results
accuracy: 1.0000 | weighted F1: 1.0000