%mavenRepo s3 https://djl-ai.s3.amazonaws.com/dev
%maven ai.djl:api:0.1.0
%maven ai.djl:repository:0.1.0
%maven ai.djl.mxnet:mxnet-engine:0.1.0
%maven ai.djl.mxnet:mxnet-model-zoo:0.1.0
%maven org.slf4j:slf4j-api:1.7.26
%maven org.slf4j:slf4j-simple:1.7.26
%maven net.java.dev.jna:jna:5.3.0
// %maven ai.djl.mxnet:mxnet-native-mkl:jar:osx-x86_64:1.6.0
%%loadFromPOM
<repositories>
<repository>
<id>djl.ai</id>
<url>https://djl-ai.s3.amazonaws.com/dev</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>ai.djl.mxnet</groupId>
<artifactId>mxnet-native-mkl</artifactId>
<version>1.6.0</version>
<classifier>osx-x86_64</classifier>
</dependency>
</dependencies>
import java.awt.image.*;
import java.nio.file.*;
import java.util.*;
import ai.djl.*;
import ai.djl.inference.*;
import ai.djl.ndarray.*;
import ai.djl.ndarray.index.*;
import ai.djl.modality.*;
import ai.djl.modality.cv.*;
import ai.djl.modality.cv.util.*;
import ai.djl.mxnet.zoo.*;
import ai.djl.util.*;
var userHome = System.getProperty("user.home");
var imageFile = Paths.get("../examples/src/test/resources/kitten.jpg").toRealPath();
var img = BufferedImageUtils.fromFile(imageFile);
img
var criteria = new HashMap<String, String>();
criteria.put("layers", "18");
criteria.put("flavor", "v1");
var model = MxModelZoo.RESNET.loadModel(criteria);
var predictor = model.newPredictor();
var classification = predictor.predict(img);
var top3 = classification.topK(3);
top3
var className = top3.get(0).getClassName();
var probability = top3.get(0).getProbability();
className + ": " + probability