Description
Pretrained ConvNext model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.
The ConvNeXT model was proposed in A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
Predicted Entities
How to use
image_assembler = ImageAssembler()\
.setInputCol("image")\
.setOutputCol("image_assembler")
imageClassifier = ConvNextForImageClassification.pretrained("image_classifier_convnext_tiny_224_local", "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 = ConvNextForImageClassification
.pretrained("image_classifier_convnext_tiny_224_local", "en")
.setInputCols("image_assembler")
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
val pipelineModel = pipeline.fit(imageDF)
val pipelineDF = pipelineModel.transform(imageDF)
Model Information
| Model Name: | image_classifier_convnext_tiny_224_local |
| Compatibility: | Spark NLP 4.4.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [image_assembler] |
| Output Labels: | [class] |
| Language: | en |
| Size: | 107.6 MB |