This is a TensorFlow* version of
densenet-161 model, one of the DenseNet group of models designed to perform image classification. The weights were converted from DenseNet-Keras Models. For details see repository, paper.
Placeholder , shape: [1x224x224x3], format: [BxHxWxC], where:
Expected color order: RGB. Mean values: [123.68, 116.78, 103.94], scale factor for each channel: 58.8235294
Placeholder, shape: [1x3x224x224], format: [BxCxHxW], where:
Expected color order: BGR.
Floating point values in range [0, 1], which represent probabilities for classes in a dataset. Name:
Floating point values in a range [0, 1], which represent probabilities for classes in a dataset. Name:
densenet161/predictions/Reshape_1/Transpose, shape: [1, 1, 1, 1000].
You can download models and if necessary convert them into Inference Engine format using the Model Downloader and other automation tools as shown in the examples below.
An example of using the Model Downloader:
An example of using the Model Converter: