English image_classifier_vit_ak__base_patch16_224_in21k_image_classification ViTForImageClassification from amitkayal

Description

Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_ak__base_patch16_224_in21k_image_classification is a English model originally trained by amitkayal.

Predicted Entities

1647932708266, 1647153073068, 1648120851131, 1647323870424, 1647324831223, 1648529040870, 1647667510657, 1647838548516, 1647491988625, 1647068900550, 1647241002660, 1647155940977, 1648444866188, 1648287279256, 1648360065352, 1646891748795, 1647175174130, 1647667513009, 1647503446037, 1648616524252, 1647241522127, 1648454681973, 1647581857611, 1647233597062, 1647933757599, 1647420385320, 1648361316938, 1647856085470, 1647243922705, 1647497162634, 1647237935761, 1648369037326, 1648115339027, 1647153746047, 1648273037858, 1647150662937, 1646893741640, 1647845708343, 1647147746930, 1648366090438, 1647156193650, 1648537457250, 1647149733777, 1648443306030, 1648646879260, 1648001685069, 1648528121469, 1647156345180, 1648456544611, 1648107120561, 1648359826755, 1648366661601, 1647666899143, 1647935446369, 1647668429439, 1647936918167, 1647235612241, 1648041520955, 1647243637048, 1647680921307, 1647081327122, 1647087753595, 1648528673166, 1648710643516, 1647945116578, 1647846670493, 1648536302434, 1647761641671, 1647325936506, 1647325395017, 1647234311073, 1647759532201, 1647241685563, 1647935761690, 1647846942176, 1648698605364, 1647933173332, 1647420602021, 1647159771571, 1647324549954, 1647065648037, 1648536755030, 1647924696448, 1647927510285, 1646892894926, 1647580734898, 1648287633901, 1648442962568, 1648368434262, 1646988520214, 1648279394220, 1647150432271, 1648643933549, 1647448253535, 1647929786244, 1648370352609, 1647330838532, 1647147396410, 1648644032811, 1647140664832, 1648536664835, 1647410160165, 1647164611497, 1648183419560, 1647773005511, 1646034720737, 1647328253213, 1647155473555, 1647953067595, 1648538213890, 1647409255750, 1647682028193, 1648116419206, 1647329803500, 1647154529007, 1648099843046, 1647248948963, 1648279061829, 1648296194026, 1648108046332, 1648113127522, 1648455583722, 1647761642926, 1648533677853, 1647940472293, 1648701651498, 1648456403645, 1647752727972, 1647494398054, 1647674319450, 1646887547179, 1647158162746, 1647176402807, 1647065469305, 1647838279102, 1647674991869, 1648113569157, 1647067760203, 1648365815895, 1647330963213, 1647405478288, 1648372401817, 1648103720352, 1648115162538, 1647784242846, 1647402768175, 1647490410305, 1648286780106, 1648625933250, 1648534124563, 1647173945909, 1647235889634, 1648525350277, 1647236596892, 1648292928751, 1648706018510, 1648024698508, 1648707239343, 1647767885862, 1647240848064, 1648280849373, 1648406457408, 1647236473208, 1647157232763, 1647147535719, 1648706506117, 1648706245642, 1647933556772, 1648616269757, 1646809025517, 1647420348512, 1647399162926, 1647843749559, 1647242632376, 1648182014371, 1647321722450, 1648369375824, 1647331957791, 1647494265176, 1647252866283, 1647930894634, 1646809256434, 1648537084774, 1648450201448, 1646885340637, 1647760733996, 1648287529293

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_ak__base_patch16_224_in21k_image_classification", "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_ak__base_patch16_224_in21k_image_classification", "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.ak__base_patch16_224_in21k_image_classification").predict("hen.JPEG")