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image classification try / published by https://github.com/dacr/code-examples-manager #32c4a82b-8a40-480a-bad9-5390bceed3dd/e4b81c417ccec91a396367f4125adeeb4e6b1923
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// summary : image classification try | |
// keywords : djl, machine-learning, tutorial, detection, ai, @testable | |
// publish : gist | |
// authors : David Crosson | |
// license : Apache NON-AI License Version 2.0 (https://raw.githubusercontent.com/non-ai-licenses/non-ai-licenses/main/NON-AI-APACHE2) | |
// id : 32c4a82b-8a40-480a-bad9-5390bceed3dd | |
// created-on : 2022-03-09T20:17:01+01:00 | |
// managed-by : https://github.com/dacr/code-examples-manager | |
// run-with : scala-cli $file | |
// --------------------- | |
//> using scala "3.3.1" | |
//> using dep "org.slf4j:slf4j-api:2.0.11" | |
//> using dep "org.slf4j:slf4j-simple:2.0.11" | |
//> using dep "net.java.dev.jna:jna:5.14.0" | |
//> using dep "ai.djl:api:0.26.0" | |
//> using dep "ai.djl:basicdataset:0.26.0" | |
//> using dep "ai.djl:model-zoo:0.26.0" | |
//> using dep "ai.djl.huggingface:tokenizers:0.26.0" | |
//> using dep "ai.djl.mxnet:mxnet-engine:0.26.0" | |
//> using dep "ai.djl.mxnet:mxnet-model-zoo:0.26.0" | |
//> using dep "ai.djl.pytorch:pytorch-engine:0.26.0" | |
//> using dep "ai.djl.pytorch:pytorch-model-zoo:0.26.0" | |
//> using dep "ai.djl.tensorflow:tensorflow-engine:0.26.0" | |
//> using dep "ai.djl.tensorflow:tensorflow-model-zoo:0.26.0" | |
//> using dep "ai.djl.paddlepaddle:paddlepaddle-engine:0.26.0" | |
//> using dep "ai.djl.paddlepaddle:paddlepaddle-model-zoo:0.26.0" | |
//> using dep "ai.djl.onnxruntime:onnxruntime-engine:0.26.0" | |
// --------------------- | |
//System.setProperty("org.slf4j.simpleLogger.defaultLogLevel", "debug") | |
import ai.djl.Application | |
import ai.djl.engine.Engine | |
import ai.djl.modality.Classifications | |
import ai.djl.modality.Classifications.Classification | |
import ai.djl.modality.cv.Image | |
import ai.djl.modality.cv.ImageFactory | |
import ai.djl.repository.zoo.Criteria | |
import ai.djl.repository.zoo.ModelZoo | |
import ai.djl.repository.zoo.ZooModel | |
import ai.djl.training.util.ProgressBar | |
import java.nio.file.Files | |
import java.nio.file.Path | |
import java.nio.file.Paths | |
import scala.jdk.CollectionConverters.* | |
// ---------------------------------------------------------------------------------------------- | |
val criteria = | |
Criteria.builder | |
.optApplication(Application.CV.IMAGE_CLASSIFICATION) | |
.setTypes(classOf[Image], classOf[Classifications]) | |
// ------------------------------------ | |
//.optFilter("flavor","v1") | |
//.optFilter("dataset","cifar10") | |
// ------------------------------------ | |
//.optFilter("flavor","v3_large") | |
//.optFilter("dataset","imagenet") | |
// ------------------------------------ | |
.optFilter("flavor","v1d") | |
.optFilter("dataset","imagenet") | |
.optProgress(new ProgressBar) | |
.build | |
val model = ModelZoo.loadModel(criteria) | |
val predictor = model.newPredictor() | |
val inputImageURL = "https://mapland.fr/data/ai/images-samples/example-001.jpg" | |
val img = ImageFactory.getInstance().fromUrl(inputImageURL) | |
val found: Classifications = predictor.predict(img) | |
found.items() | |
.asScala | |
.toList | |
.asInstanceOf[List[Classification]] | |
.filter(_.getProbability > 0.5d) | |
.foreach{cl => | |
println(cl.getClassName+" "+cl.getProbability) | |
} |
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