resnet-101

Use Case and High-Level Description

ResNet-101

Example

Specification

Metric Value
Type Classification
GFLOPs 14.441
MParams 44.496
Source framework Caffe*

Accuracy

Metric Value
Top 1 76.364%
Top 5 92.902%

See the original repository.

Performance

Input

Original Model

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

Channel order is BGR. Mean values: [104, 117, 123].

Converted Model

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

Channel order is BGR.

Output

Original Model

Object classifier according to ImageNet classes, name: prob, shape: 1,1000, output data format is B,C where:

Converted Model

Object classifier according to ImageNet classes, name: prob, shape: 1,1000, output data format is B,C where:

Legal Information

The original model is distributed under the following license:

The MIT License (MIT)
Copyright (c) 2016 Shaoqing Ren
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.