README_en.md

shufflenet_v2_imagenet

Module Name	shufflenet_v2_imagenet
Category	image classification
Network	ShuffleNet V2
Dataset	ImageNet-2012
Fine-tuning supported or not	No
Module Size	11MB
Latest update date	-
Data indicators	-

I.Basic Information

• Module Introduction

  • ShuffleNet V2 is a light-weight model proposed by MEGVII in 2018. This model proposed pointwise group convolution and channel shuffle to keep accurary and reduce the amount of computation. This module is based on ShuffleNet V2, trained on ImageNet-2012, and can predict an image of 2242243.

II.Installation

• 1、Environmental Dependence

  • paddlepaddle >= 1.4.0

  • paddlehub >= 1.0.0 | How to install PaddleHub

• 2、Installation

  • $ hub install shufflenet_v2_imagenet

  • In case of any problems during installation, please refer to: Windows_Quickstart | Linux_Quickstart | Mac_Quickstart

III.Module API Prediction

• 1、Command line Prediction

  • $ hub run shufflenet_v2_imagenet --input_path "/PATH/TO/IMAGE"

  • If you want to call the Hub module through the command line, please refer to: PaddleHub Command Line Instruction

• 2、Prediction Code Example

  • import paddlehub as hub
    import cv2
    
    classifier = hub.Module(name="shufflenet_v2_imagenet")
    test_img_path = "/PATH/TO/IMAGE"
    input_dict = {"image": [test_img_path]}
    result = classifier.classification(data=input_dict)

• 3、API

  • def classification(data)

    • classification API.

    • Parameters

      • data (dict): key is "image", value is a list of image paths

    • Return

      • result(list[dict]): classication results, each element in the list is dict, key is the label name, and value is the corresponding probability

IV.Release Note

• 1.0.0

  First release

  • $ hub install shufflenet_v2_imagenet==1.0.0