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DJL Spark Image Example

Introduction

This folder contains 3 demo applications built with Spark and DJL to run image related tasks.

  • ImageClassificationExample: Ready to run for image classification using built in model from Model URL
  • ObjectDetectionExample: Ready to run for object detection using built in model from Model URL
  • SemanticSegmentationExample: Ready to run for semantic segmentation using built in model from Model URL

Setup

We provide two options to build, you can choose to build with sbt or gradle.

sbt

libraryDependencies += "ai.djl.spark" % "spark_2.12" % "0.30.0"
libraryDependencies += "ai.djl.pytorch" % "pytorch-engine" % "0.30.0"
libraryDependencies += "ai.djl.pytorch" % "pytorch-model-zoo" % "0.30.0"
libraryDependencies += "ai.djl.pytorch" % "pytorch-native-cpu-precxx11" % "2.4.0"

gradle

You should add these in dependencies

dependencies {
    implementation platform("ai.djl:bom:${djl_version}")
    implementation "ai.djl.spark:spark_2.12"
    runtimeOnly "ai.djl.pytorch:pytorch-engine"
    runtimeOnly "ai.djl.pytorch:pytorch-model-zoo"
    runtimeOnly "ai.djl.pytorch:pytorch-native-cpu-precxx11"
}

Run the example

Use spark-submit to run the examples. For example, to run the image classification example, you can run:

spark-submit --class com.examples.ImageClassificationExample \
    --master yarn \
    --mode cluster \
    --conf spark.executor.instances=2 \
    --conf spark.executor.memory=2G \
    --conf spark.executor.cores=2 \
    --conf spark.driver.memory=1G \
    --conf spark.driver.cores=1 \
    build/libs/image-1.0-SNAPSHOT-all.jar