Description
Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_gtsrb_model is a English model originally trained by bazyl.
Predicted Entities
Children crossing, Double curve, Road work, Yield, Beware of ice/snow, Speed limit (70km/h), Bicycles crossing, Roundabout mandatory, Speed limit (30km/h), Keep left, Dangerous curve left, No vehicles, End of no passing, Bumpy road, Speed limit (50km/h), Turn left ahead, Speed limit (20km/h), General caution, Speed limit (100km/h), End speed + passing limits, Go straight or right, Dangerous curve right, Speed limit (80km/h), Slippery road, Turn right ahead, No passing veh over 3.5 tons, Speed limit (60km/h), Pedestrians, Right-of-way at intersection, Priority road, End of speed limit (80km/h), Road narrows on the right, No entry, Stop, Wild animals crossing, Veh > 3.5 tons prohibited, End no passing veh > 3.5 tons, Go straight or left, Speed limit (120km/h), Ahead only, Keep right, Traffic signals, No passing
How to use
pipeline = PretrainedPipeline('pipeline_image_classifier_vit_gtsrb_model', lang = 'en')
annotations = pipeline.transform(imageDF)
val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_gtsrb_model", lang = "en")
val annotations = pipeline.transform(imageDF)
Model Information
| Model Name: | pipeline_image_classifier_vit_gtsrb_model |
| Type: | pipeline |
| Compatibility: | Spark NLP 4.2.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 322.0 MB |
Included Models
- ImageAssembler
- ViTForImageClassification