English image_classifier_vit_iiif_manuscript_ ViTForImageClassification from davanstrien

Description

Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_iiif_manuscript_ is a English model originally trained by davanstrien.

Predicted Entities

3rd upper flyleaf verso, Blank leaf recto, 3rd lower flyleaf verso, 2nd lower flyleaf verso, 2nd upper flyleaf verso, flyleaf, 1st upper flyleaf verso, 1st lower flyleaf verso, fol, cover, Lower flyleaf verso, Blank leaf verso, Upper flyleaf verso

Live Demo Open in Colab Download Copy S3 URI

How to use

image_assembler = ImageAssembler() \
    .setInputCol("image") \
    .setOutputCol("image_assembler")

imageClassifier = ViTForImageClassification \
    .pretrained("image_classifier_vit_iiif_manuscript_", "en")\
    .setInputCols("image_assembler") \
    .setOutputCol("class")

pipeline = Pipeline(stages=[
    image_assembler,
    imageClassifier,
])

pipelineModel = pipeline.fit(imageDF)

pipelineDF = pipelineModel.transform(imageDF)

val imageAssembler = new ImageAssembler()
.setInputCol("image")
.setOutputCol("image_assembler")

val imageClassifier = ViTForImageClassification
.pretrained("image_classifier_vit_iiif_manuscript_", "en")
.setInputCols("image_assembler")
.setOutputCol("class")

val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))

val pipelineModel = pipeline.fit(imageDF)

val pipelineDF = pipelineModel.transform(imageDF)

import nlu
import requests
response = requests.get('https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/docs/assets/images/hen.JPEG')
with open('hen.JPEG', 'wb') as f:
    f.write(response.content)
nlu.load("en.classify_image.iiif_manuscript_").predict("hen.JPEG")