image classification try / published by https://github.com/dacr/code-examples-manager #32c4a82b-8a40-480a-bad9-5390bceed3dd/c49b6ec266249eb67d7c6866045612a1304a06cb

djl-image-classification.sc

// 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 "3.4.2"
//> using dep "org.slf4j:slf4j-api:2.0.13"
//> using dep "org.slf4j:slf4j-simple:2.0.13"
//> using dep "net.java.dev.jna:jna:5.14.0"

//> using dep "ai.djl:api:0.29.0"
//> using dep "ai.djl:basicdataset:0.29.0"
//> using dep "ai.djl:model-zoo:0.29.0"
//> using dep "ai.djl.huggingface:tokenizers:0.29.0"

//> using dep "ai.djl.mxnet:mxnet-engine:0.29.0"
//> using dep "ai.djl.mxnet:mxnet-model-zoo:0.29.0"

//> using dep "ai.djl.pytorch:pytorch-engine:0.29.0"
//> using dep "ai.djl.pytorch:pytorch-model-zoo:0.29.0"

//> using dep "ai.djl.tensorflow:tensorflow-engine:0.29.0"
//> using dep "ai.djl.tensorflow:tensorflow-model-zoo:0.29.0"

//> using dep "ai.djl.onnxruntime:onnxruntime-engine:0.29.0"
// ---------------------

//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)
}