Class DenseNet201

DenseNet models, with weights pre-trained on ImageNet. This model and can be built both with 'channels_first' data format(channels, height, width) or 'channels_last' data format(height, width, channels). The default input size for this model is 224x224.

Inheritance
System.Object
Keras
Base
BaseModel
Model
AppModelBase
DenseNet201
Implements
System.IDisposable
Inherited Members
System.Object.Equals(System.Object)
System.Object.Equals(System.Object, System.Object)
System.Object.GetHashCode()
System.Object.GetType()
System.Object.MemberwiseClone()
System.Object.ReferenceEquals(System.Object, System.Object)
System.Object.ToString()
Namespace: Keras.Applications.DenseNet
Assembly: Keras.dll
Syntax
public class DenseNet201 : AppModelBase, IDisposable

Constructors

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DenseNet201(Int32, Boolean, String, NDarray, Shape, String, Int32)

Initializes a new instance of the DenseNet201 class.

Declaration
public DenseNet201(int blocks, bool include_top = true, string weights = "imagenet", NDarray input_tensor = null, Shape input_shape = null, string pooling = "None", int classes = 1000)
Parameters
Type Name Description
System.Int32 blocks

numbers of building blocks for the four dense layers.
System.Boolean include_top

optional shape tuple, only to be specified if include_top is False (otherwise the input shape has to be (224, 224, 3) (with 'channels_last' data format) or (3, 224, 224) (with 'channels_first' data format) for NASNetMobile or (331, 331, 3) (with 'channels_last' data format) or (3, 331, 331) (with 'channels_first' data format) for NASNetLarge. It should have exactly 3 inputs channels, and width and height should be no smaller than 32. E.g. (200, 200, 3) would be one valid value.
System.String weights

one of None (random initialization), 'imagenet' (pre-training on ImageNet), or the path to the weights file to be loaded.
Numpy.NDarray input_tensor

optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model.
Shape input_shape

optional shape tuple, only to be specified if include_top is False (otherwise the input shape has to be (224, 224, 3) (with 'channels_last' data format) or (3, 224, 224) (with 'channels_first' data format). It should have exactly 3 inputs channels, and width and height should be no smaller than 32. E.g. (200, 200, 3) would be one valid value.
System.String pooling

optional pooling mode for feature extraction when include_top is False. None means that the output of the model will be the 4D tensor output of the last convolutional layer. avg means that global average pooling will be applied to the output of the last convolutional layer, and thus the output of the model will be a 2D tensor. max means that global max pooling will be applied.
System.Int32 classes

optional number of classes to classify images into, only to be specified if include_top is True, and if no weights argument is specified.

Implements

System.IDisposable