Description
Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_snacks is a English model originally trained by Shivagowri.
Predicted Entities
salad, candy, muffin, banana, grape, popcorn, pretzel, pineapple, juice, orange, doughnut, carrot, waffle, cake, cookie, ice cream, watermelon, hot dog, apple, strawberry
How to use
pipeline = PretrainedPipeline('pipeline_image_classifier_vit_snacks', lang = 'en')
annotations = pipeline.transform(imageDF)
val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_snacks", lang = "en")
val annotations = pipeline.transform(imageDF)
Model Information
| Model Name: | pipeline_image_classifier_vit_snacks |
| Type: | pipeline |
| Compatibility: | Spark NLP 4.2.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 322.0 MB |
Included Models
- ImageAssembler
- ViTForImageClassification