Description
Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy is a English model originally trained by mrm8488.
Predicted Entities
ulcerative-colitis, normal-pylorus, normal-cecum, normal-z-line, esophagitis, dyed-lifted-polyps, dyed-resection-margins, polyps
How to use
pipeline = PretrainedPipeline('pipeline_image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy', lang = 'en')
annotations = pipeline.transform(imageDF)
val pipeline = new PretrainedPipeline("pipeline_image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy", lang = "en")
val annotations = pipeline.transform(imageDF)
Model Information
| Model Name: | pipeline_image_classifier_vit_base_patch16_224_finetuned_kvasirv2_colonoscopy |
| Type: | pipeline |
| Compatibility: | Spark NLP 4.2.1+ |
| License: | Open Source |
| Edition: | Official |
| Language: | en |
| Size: | 321.9 MB |
Included Models
- ImageAssembler
- ViTForImageClassification