resnet-50-caffe2

Use Case and High-Level Description

This is a Caffe2* version of the ResNet-50 model, designed to perform image classification. This model was converted from Caffe* to Caffe2* format. For details see repository, paper.

Specification

Metric Value
Type Classification
GFLOPs 8.216
MParams 25.53
Source framework Caffe2*

Accuracy

Metric Value
Top 1 76.38%
Top 5 93.188%

Input

Original model

Image, name - gpu_0/data, shape - 1, 3, 224, 224, format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is BGR. Mean values - [103.53, 116.28, 123.675], scale values - [57.375, 57.12, 58.395].

Converted model

Image, name - gpu_0/data, shape - 1, 3, 224, 224, format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is BGR.

Output

Original model

Object classifier according to ImageNet classes, name - gpu_0/softmax, shape - 1, 1000, output data format is B, C, where:

  • B - batch size
  • C - predicted probabilities for each class in [0, 1] range

Converted model

Object classifier according to ImageNet classes, name - gpu_0/softmax, shape - 1, 1000, output data format is B, C, where:

  • B - batch size
  • C - predicted probabilities for each class in [0, 1] range

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 APACHE-2.0.txt.