densenet-201-tf¶
Use Case and High-Level Description¶
This is a TensorFlow* version of densenet-201
model, one of the DenseNet group of models designed to perform image classification. For details, see TensorFlow* API docs, repository and paper.
Specification¶
Metric |
Value |
---|---|
Type |
Classification |
GFlops |
8.6786 |
MParams |
20.0013 |
Source framework |
TensorFlow* |
Accuracy¶
Metric |
Value |
---|---|
Top 1 |
76.93% |
Top 5 |
93.56% |
Input¶
Original Model¶
Image, name: input_1
, shape: 1, 224, 224, 3
, format: B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Expected color order: RGB
. Mean values - [123.68, 116.78, 103.94], scale values - [58.395,57.12,57.375].
Converted Model¶
Image, name: input_1
, shape: 1, 3, 224, 224
, format: B, C, H, W
, where:
B
- batch sizeC
- number of channelsH
- image heightW
- image width
Expected color order: BGR
.
Output¶
Original Model¶
Object classifier according to ImageNet classes, name: StatefulPartitionedCall/densenet201/predictions/Softmax
, shape: 1, 1000
, output data format is B, C
, where:
B
- batch sizeC
- predicted probabilities for each class in [0, 1] range
Converted Model¶
The converted model has the same parameters as the original model.
Download a Model and Convert it into Inference Engine Format¶
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:
python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>
An example of using the Model Converter:
python3 <omz_dir>/tools/downloader/converter.py --name <model_name>
Legal Information¶
The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0-TensorFlow.txt
.