README_en.md

spinalnet_res101_gemstone

Module Name	spinalnet_res101_gemstone
Category	image classification
Network	resnet101
Dataset	gemstone
Fine-tuning supported or not	No
Module Size	246MB
Latest update date	-
Data indicators	-

I.Basic Information

• Module Introduction

  • This module is based on SpinalNet trained on gemstone dataset, and can be used to classify a gemstone.

II.Installation

• 1、Environmental Dependence

  • paddlepaddle >= 2.0.0

  • paddlehub >= 2.0.0 | How to install PaddleHub

• 2、Installation

  • $ hub install spinalnet_res101_gemstone

  • 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 spinalnet_res101_gemstone --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="spinalnet_res101_gemstone")
    result = classifier.predict(['/PATH/TO/IMAGE'])
    print(result)

• 3、API

  • def predict(images)

    • classification API.

    • Parameters

      • images(list[numpy.ndarray]): image data.

    • 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 spinalnet_res101_gemstone==1.0.0