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0.4.0 (01/06/2022) Pose Detection, EfficientDet for Object Detection and EfficientNet for Image Recognition

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@zaleslaw zaleslaw released this 09 Jun 14:03
· 183 commits to master since this release

Features:

  • Added the PoseNet model family to the ONNX Model Hub. #269
    • MoveNetSinglePoseLighting
    • MoveNetMultiPoseLighting
    • MoveNetSinglePoseThunder
  • Added the EfficientDet model family to the ONNX Model Hub. #304
    • EfficientDetD0
    • EfficientDetD1
    • EfficientDetD2
    • EfficientDetD3
    • EfficientDetD4
    • EfficientDetD5
    • EfficientDetD6
  • Added SSD-Mobilenet-v1 model to the ONNX Model Hub. #296
  • Added EfficientNet model family to the ONNX Model Hub. #264
    • EfficientNetB0 ( + noTop model)
    • EfficientNetB1 ( + noTop model)
    • EfficientNetB2 ( + noTop model)
    • EfficientNetB3 ( + noTop model)
    • EfficientNetB4 ( + noTop model)
    • EfficientNetB5 ( + noTop model)
    • EfficientNetB6 ( + noTop model)
    • EfficientNetB7 ( + noTop model)
  • Added NoTop models to the TensorFlow Model Hub. #281
    • VGG'16
    • VGG'19
    • ResNet50
    • ResNet101
    • ResNet152
    • ResNet50V2
    • ResNet101V2
    • ResNet152V2
    • MobileNet
    • MobileNetV2
    • NasNetMobile
    • NasNetLarge
    • DenseNet121
    • DenseNet169
    • DenseNet201
    • Xception
    • Inception
  • Added new Dot layer and Conv1DTranspose, Conv2DTranspose, Conv3DTranspose layers.
    #144 #124
  • Added new activation functions: SparsemaxActivation and SoftShrinkActivation.
    #171 #170
  • Added new Padding, CenterCrop, Convert, Grayscale image preprocessors and Normalizing tensor preprocessor.
    #203 #201
    #202 #204

Examples and tutorials:

API changes:

  • Introduced new DSL for creating Sequential and Functional models. #133
  • Added support for multiple Callbacks in fit(), evaluate(), predict() instead of compile().
    #270
  • Added support for multiple metrics. #298
  • Added support for the model reset. #271
  • Replaced Long parameters with Integer ones in convolutional, average pool and max pool layers.
    #273
  • Moved loading section out of image preprocessing. #322
  • Remove obsolete CustomPreprocessor interface. #257
  • Supported exporting tensor data to BufferedImage #293

Internal API changes:

  • Introduced new abstraction for layer parameters -- KVariable. #324
  • Moved some of the Layer functionality to the new interfaces ParametrizedLayer and TrainableLayer.
    #217

Bug fixes:

  • Added support for correct loading of isTrainable status from Keras. #153
  • Generalized Reshape layer to higher dimensions. #249
  • Fixed incorrect bounding box coordinates in ObjectDetection and FaceDetection examples. #279
  • Fixed toString methods for layer classes. #301
  • Set all the optimizers to have useLocking = True #305
  • Fixed a bug with silently skipped layers in topological sort. #314
  • Fixed loadModelLayersFromConfiguration recursively calling itself. #319
  • Fixed GraphTrainableModel#internalPredict for multi-dimensional predictions. #327
  • Fixed Orthogonal initializer. #348
  • Fixed initialization of the variables in GraphTrainableModel. #355
  • Add model output type checks for OnnxInferenceModel. #356
  • Fixed IndexOutOfBoundsException in the Dot layer. #357
  • Fixed import and export issues:
    • Fixed layers import and export and added tests. #329
      #341 #360
    • Fixed exporting Ones, Zeros, Orthogonal and ParametrizedTruncatedNormal initializers.
      #331
  • Updated log4j version.
  • Fixed the group of examples with ToyResNet.

Thanks to our contributors: