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- 【人脸检测】新增6个模型(MTCNN、YOLOV5、RetinaFace小尺寸版)，大幅提升性能

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- 【人脸识别】新增Seetaface6轻量模型
- 【目标检测】支持视频流目标检测（rtsp、视频文件等）
- 【目标检测】支持tensorflow2目标检测模型
- 【目标检测】新增行人检测模型(yolo-person)
- 【通用视觉】新增4个动作识别模型
- 【通用视觉】新增语义分割模型
- 【通用视觉】新增5个实例分割模型(含yolov8-seg、yolov11-seg)
- 【通用视觉】新增yolo-obb11旋转框检测(含yolov11-obb)
- 【通用视觉】新增5个姿态估计模型(含yolov8-pose、yolov11-pose)
This commit is contained in:
dengwenjie
2025-09-07 17:19:19 +08:00
parent 2b044fda29
commit a8e7ce6c4e
102 changed files with 4473 additions and 1368 deletions
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49
vision/src/main/java/cn/smartjavaai/instanceseg/criteria/InstanceSegCriteriaFactory.java
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@@ -3,10 +3,12 @@ package cn.smartjavaai.instanceseg.criteria;
import ai.djl.Device;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.output.DetectedObjects;
import ai.djl.modality.cv.translator.InstanceSegmentationTranslatorFactory;
import ai.djl.repository.zoo.Criteria;
import ai.djl.training.util.ProgressBar;
import cn.smartjavaai.common.enums.DeviceEnum;
import cn.smartjavaai.instanceseg.config.InstanceSegModelConfig;
import cn.smartjavaai.instanceseg.enums.InstanceSegModelEnum;
import cn.smartjavaai.instanceseg.translator.YoloSegmentationTranslatorFactory2;
import org.apache.commons.lang3.StringUtils;
@@ -27,21 +29,42 @@ public class InstanceSegCriteriaFactory {
device = config.getDevice() == DeviceEnum.CPU ? Device.cpu() : Device.gpu(config.getGpuId());
}
Criteria<Image, DetectedObjects> criteria = null;
ConcurrentHashMap params = new ConcurrentHashMap<String, String>();
params.putAll(config.getCustomParams());
// ConcurrentHashMap params = new ConcurrentHashMap<String, String>();
// params.putAll(config.getCustomParams());
// YoloV5Translator.Builder builder = new YoloV5Translator.Builder()
// .optSynsetArtifactName("synset.txt").setPipeline()
criteria =
Criteria.builder()
.setTypes(Image.class, DetectedObjects.class)
.optModelUrls(StringUtils.isNotBlank(config.getModelPath()) ? null :
config.getModelEnum().getModelUri())
.optModelPath(StringUtils.isNotBlank(config.getModelPath()) ? Paths.get(config.getModelPath()) : null)
.optDevice(device)
.optEngine("PyTorch")
.optTranslatorFactory(new YoloSegmentationTranslatorFactory2())
.optProgress(new ProgressBar())
.build();
if(config.getModelEnum() == InstanceSegModelEnum.SEG_MASK_RCNN){
criteria =
Criteria.builder()
.setTypes(Image.class, DetectedObjects.class)
.optModelUrls(StringUtils.isNotBlank(config.getModelPath()) ? null :
config.getModelEnum().getModelUri())
.optModelPath(StringUtils.isNotBlank(config.getModelPath()) ? Paths.get(config.getModelPath()) : null)
.optDevice(device)
.optEngine(config.getModelEnum().getEngine())
.optArgument("normalize","true")
.optArgument("synsetFileName","classes.txt")
.optTranslatorFactory(new InstanceSegmentationTranslatorFactory())
.optProgress(new ProgressBar())
.build();
}else{
criteria =
Criteria.builder()
.setTypes(Image.class, DetectedObjects.class)
.optModelUrls(StringUtils.isNotBlank(config.getModelPath()) ? null :
config.getModelEnum().getModelUri())
.optModelPath(StringUtils.isNotBlank(config.getModelPath()) ? Paths.get(config.getModelPath()) : null)
.optDevice(device)
.optArgument("width", config.getModelEnum().getInputWidth())
.optArgument("height", config.getModelEnum().getInputHeight())
.optArgument("resize", "true")
.optArgument("threshold", config.getThreshold())
.optEngine(config.getModelEnum().getEngine())
.optTranslatorFactory(new YoloSegmentationTranslatorFactory2())
.optProgress(new ProgressBar())
.build();
}
return criteria;
}
}