This is a TensorFlow* version of densenet-169 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 and paper.
| Metric | Value |
|---|---|
| Type | Classification |
| GFlops | 6.16 |
| MParams | 14.139 |
| Source framework | TensorFlow* |
| Metric | Value |
|---|---|
| Top 1 | 75.76% |
| Top 5 | 92.81% |
Name: Placeholder , shape: [1x224x224x3]. An input image is the [BxHxWxC] format,
where:
- B - batch size
- H - image height
- W - image width
- C - number of channels
Expected color order: RGB. Mean values: [123.68, 116.78, 103.94], scale factor for each channel: 58.8235294
Name: Placeholder, shape: [1x3x224x224]. An input image is in the [BxCxHxW] format,
where:
- B - batch size
- C - number of channels
- H - image height
- W - image width
Expected color order: BGR.
Name:densenet169/predictions/Reshape_1. Contains floating point values in a range [0, 1], which represent probabilities for classes in a dataset.
Name: densenet169/predictions/Reshape_1/Transpose, shape: [1, 1, 1, 1000]. Contains floating point values in a range [0, 1], which represent probabilities for classes in a dataset.
The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in APACHE-2.0-TF-DenseNet.txt.