Description
Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_world_landmarks is a English model originally trained by mmgyorke.
Predicted Entities
la sagrada familia, leaning tower of pisa, arc de triomphe, taj mahal, big ben
How to use
pipeline = PretrainedPipeline('pipeline_image_classifier_vit_world_landmarks', lang = 'en')
annotations = pipeline.transform(imageDF)
val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_world_landmarks", lang = "en")
val annotations = pipeline.transform(imageDF)
Model Information
| Model Name: | pipeline_image_classifier_vit_world_landmarks |
| Type: | pipeline |
| Compatibility: | Spark NLP 4.2.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 321.9 MB |
Included Models
- ImageAssembler
- ViTForImageClassification