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Image AutoML with AutoGluon, Sign Identification
Dataset: ecopus/sign_identification
Task: multiclass image classification using AutoGluon Multimodal.
Training
- Preset: medium_quality
- Backbone: timm_image, resnet18
- Split: augmented 80 percent train, 20 percent test
- External validation: original split
Results
- Augmented test accuracy: 1.0000
- Augmented test weighted F1: 1.0000
- Original external accuracy: 1.0000
- Original external weighted F1: 1.0000
How to load
from autogluon.multimodal import MultiModalPredictor
predictor = MultiModalPredictor.load('predictor_dir')
pred = predictor.predict({'image': ['/path/to/img.png']})
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