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[pytorch] Adds Yolov11 model to model zoo
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xyang16 committed Nov 12, 2024
1 parent 5f0e5e5 commit e18dd99
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Showing 12 changed files with 266 additions and 12 deletions.
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Expand Up @@ -30,13 +30,16 @@ public class OrtModelZoo extends ModelZoo {

OrtModelZoo() {
addModel(REPOSITORY.model(CV.IMAGE_CLASSIFICATION, GROUP_ID, "resnet", "0.0.1"));
addModel(REPOSITORY.model(CV.INSTANCE_SEGMENTATION, GROUP_ID, "yolo11n-seg", "0.0.1"));
addModel(REPOSITORY.model(CV.INSTANCE_SEGMENTATION, GROUP_ID, "yolov8n-seg", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-base-plus", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-large", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-small", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-tiny", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolo11n", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolo5s", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolov8n", "0.0.1"));
addModel(REPOSITORY.model(CV.POSE_ESTIMATION, GROUP_ID, "yolo11n-pose", "0.0.1"));
addModel(REPOSITORY.model(CV.POSE_ESTIMATION, GROUP_ID, "yolov8n-pose", "0.0.1"));
addModel(REPOSITORY.model(Tabular.SOFTMAX_REGRESSION, GROUP_ID, "iris_flowers", "0.0.1"));
}
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@@ -0,0 +1,40 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/instance_segmentation",
"groupId": "ai.djl.onnxruntime",
"artifactId": "yolo11n-seg",
"name": "yolo11n seg",
"description": "yolo11n Instance Segmentation",
"website": "http://www.djl.ai/engines/onnxruntime/onnxruntime-engine",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n-seg",
"properties": {
},
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"threshold": 0.25,
"translatorFactory": "ai.djl.modality.cv.translator.YoloSegmentationTranslatorFactory"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n-seg.zip",
"sha1Hash": "981707febd20985b4131410498c36696bb5d442e",
"name": "",
"size": 10181964
}
}
}
]
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,40 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/object_detection",
"groupId": "ai.djl.onnxruntime",
"artifactId": "yolo11n",
"name": "yolo11n",
"description": "Yolo11n Object Detection",
"website": "http://www.djl.ai/engines/onnxruntime/model-zoo",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n",
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"rescale": true,
"optApplyRatio": true,
"threshold": 0.6,
"translatorFactory": "ai.djl.modality.cv.translator.YoloV8TranslatorFactory"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n.zip",
"name": "",
"sha1Hash": "e2b16662393be2ae7ae41c641ebdb1c919675878",
"size": 9318872
}
}
}
]
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,40 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/pose_estimation",
"groupId": "ai.djl.onnxruntime",
"artifactId": "yolo11n-pose",
"name": "yolo11n pose",
"description": "yolo11n Pose Estimation",
"website": "http://www.djl.ai/engines/onnxruntime/onnxruntime-engine",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n-pose",
"properties": {
},
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"threshold": 0.25,
"translatorFactory": "ai.djl.modality.cv.translator.YoloPoseTranslatorFactory"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n-pose.zip",
"sha1Hash": "3206acb87f1a8a69eeca017639376b7549ae1e92",
"name": "",
"size": 10176054
}
}
}
]
}
Original file line number Diff line number Diff line change
Expand Up @@ -42,12 +42,15 @@ public class PtModelZoo extends ModelZoo {
addModel(REPOSITORY.model(CV.IMAGE_CLASSIFICATION, GROUP_ID, "resnet", "0.0.1"));
addModel(
REPOSITORY.model(CV.IMAGE_CLASSIFICATION, GROUP_ID, "resnet18_embedding", "0.0.1"));
addModel(REPOSITORY.model(CV.INSTANCE_SEGMENTATION, GROUP_ID, "yolo11n-seg", "0.0.1"));
addModel(REPOSITORY.model(CV.INSTANCE_SEGMENTATION, GROUP_ID, "yolov8n-seg", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-tiny", "0.0.1"));
addModel(REPOSITORY.model(CV.MASK_GENERATION, GROUP_ID, "sam2-hiera-large", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "ssd", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolo11n", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolov5s", "0.0.1"));
addModel(REPOSITORY.model(CV.OBJECT_DETECTION, GROUP_ID, "yolov8n", "0.0.1"));
addModel(REPOSITORY.model(CV.POSE_ESTIMATION, GROUP_ID, "yolo11n-pose", "0.0.1"));
addModel(REPOSITORY.model(CV.POSE_ESTIMATION, GROUP_ID, "yolov8n-pose", "0.0.1"));
addModel(REPOSITORY.model(NLP.QUESTION_ANSWER, GROUP_ID, "bertqa", "0.0.1"));
addModel(REPOSITORY.model(NLP.SENTIMENT_ANALYSIS, GROUP_ID, "distilbert", "0.0.1"));
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@@ -0,0 +1,43 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/instance_segmentation",
"groupId": "ai.djl.pytorch",
"artifactId": "yolo11n-seg",
"name": "yolo11n seg",
"description": "yolo11n Instance Segmentation",
"website": "http://www.djl.ai/engines/pytorch/pytorch-model-zoo",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n-seg",
"properties": {
},
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"threshold": 0.25,
"translatorFactory": "ai.djl.modality.cv.translator.YoloSegmentationTranslatorFactory"
},
"options": {
"mapLocation": "true"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n-seg.zip",
"sha1Hash": "22a1d6a33fb9a5da738d04fc82c2faab8104ecc7",
"name": "",
"size": 10380298
}
}
}
]
}
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@@ -0,0 +1,43 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/object_detection",
"groupId": "ai.djl.pytorch",
"artifactId": "yolo11n",
"name": "yolo11n",
"description": "Yolo11n Object Detection",
"website": "http://www.djl.ai/engines/onnxruntime/model-zoo",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n",
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"rescale": true,
"optApplyRatio": true,
"threshold": 0.6,
"translatorFactory": "ai.djl.modality.cv.translator.YoloV8TranslatorFactory"
},
"options": {
"mapLocation": "true"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n.zip",
"name": "",
"sha1Hash": "5af1900a48422b91d585bf096b1a03da310e6ed3",
"size": 9499137
}
}
}
]
}
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@@ -0,0 +1,43 @@
{
"metadataVersion": "0.2",
"resourceType": "model",
"application": "cv/pose_estimation",
"groupId": "ai.djl.pytorch",
"artifactId": "yolo11n-pose",
"name": "yolo11n pose",
"description": "yolo11n Pose Estimation",
"website": "http://www.djl.ai/engines/pytorch/pytorch-model-zoo",
"licenses": {
"license": {
"name": "The Apache License, Version 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
}
},
"artifacts": [
{
"version": "0.0.1",
"snapshot": false,
"name": "yolo11n-pose",
"properties": {
},
"arguments": {
"width": 640,
"height": 640,
"resize": true,
"threshold": 0.25,
"translatorFactory": "ai.djl.modality.cv.translator.YoloPoseTranslatorFactory"
},
"options": {
"mapLocation": "true"
},
"files": {
"model": {
"uri": "0.0.1/yolo11n-pose.zip",
"sha1Hash": "73fda7970f476d19a8daf4d0827caeaa2f203487",
"name": "",
"size": 10371051
}
}
}
]
}
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Expand Up @@ -56,7 +56,7 @@ public static DetectedObjects predict() throws IOException, ModelException, Tran
Criteria<Image, DetectedObjects> criteria =
Criteria.builder()
.setTypes(Image.class, DetectedObjects.class)
.optModelUrls("djl://ai.djl.pytorch/yolov8n-seg")
.optModelUrls("djl://ai.djl.pytorch/yolo11n-seg")
.optTranslatorFactory(new YoloSegmentationTranslatorFactory())
.optProgress(new ProgressBar())
.build();
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ public static Joints[] predict() throws IOException, ModelException, TranslateEx
Criteria<Image, Joints[]> criteria =
Criteria.builder()
.setTypes(Image.class, Joints[].class)
.optModelUrls("djl://ai.djl.pytorch/yolov8n-pose")
.optModelUrls("djl://ai.djl.pytorch/yolo11n-pose")
.optTranslatorFactory(new YoloPoseTranslatorFactory())
.build();

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Original file line number Diff line number Diff line change
Expand Up @@ -33,11 +33,11 @@
import java.nio.file.Paths;

/** An example of inference using an yolov8 model. */
public final class Yolov8Detection {
public final class YoloDetection {

private static final Logger logger = LoggerFactory.getLogger(Yolov8Detection.class);
private static final Logger logger = LoggerFactory.getLogger(YoloDetection.class);

private Yolov8Detection() {}
private YoloDetection() {}

public static void main(String[] args) throws IOException, ModelException, TranslateException {
DetectedObjects detection = predict();
Expand All @@ -49,11 +49,11 @@ public static DetectedObjects predict() throws IOException, ModelException, Tran
Image img = ImageFactory.getInstance().fromFile(imgPath);

// Use DJL OnnxRuntime model zoo model, model can be found:
// https://mlrepo.djl.ai/model/cv/object_detection/ai/djl/onnxruntime/yolov8n/0.0.1/yolov8n.zip
// https://mlrepo.djl.ai/model/cv/object_detection/ai/djl/onnxruntime/yolo11n/0.0.1/yolo11n.zip
Criteria<Path, DetectedObjects> criteria =
Criteria.builder()
.setTypes(Path.class, DetectedObjects.class)
.optModelUrls("djl://ai.djl.onnxruntime/yolov8n")
.optModelUrls("djl://ai.djl.onnxruntime/yolo11n")
.optEngine("OnnxRuntime")
.optArgument("width", 640)
.optArgument("height", 640)
Expand All @@ -76,7 +76,7 @@ public static DetectedObjects predict() throws IOException, ModelException, Tran
DetectedObjects detection = predictor.predict(imgPath);
if (detection.getNumberOfObjects() > 0) {
img.drawBoundingBoxes(detection);
Path output = outputPath.resolve("yolov8_detected.png");
Path output = outputPath.resolve("yolo_detected.png");
try (OutputStream os = Files.newOutputStream(output)) {
img.save(os, "png");
}
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Original file line number Diff line number Diff line change
Expand Up @@ -23,18 +23,17 @@

import java.io.IOException;

public class Yolov8DetectionTest {
public class YoloDetectionTest {

@Test
public void testYolov8Detection() throws ModelException, TranslateException, IOException {
TestRequirements.notGpu();

DetectedObjects result = Yolov8Detection.predict();
DetectedObjects result = YoloDetection.predict();

Assert.assertTrue(result.getNumberOfObjects() >= 1);
Assert.assertTrue(result.getClassNames().contains("dog"));
Classifications.Classification obj = result.best();
String className = obj.getClassName();
Assert.assertEquals(className, "dog");
Assert.assertTrue(obj.getProbability() > 0.6);
}
}

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