Dataset之Knifey-Spoony：Knifey-Spoony數(shù)據(jù)集的簡介、下載、使用方法之詳細攻略

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目錄

Knifey-Spoony數(shù)據(jù)集的簡介

##The Knifey-Spoony Data-Set

## Introduction

## Images

Knifey-Spoony數(shù)據(jù)集的下載

Knifey-Spoony數(shù)據(jù)集的使用方法

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Knifey-Spoony數(shù)據(jù)集的簡介

? ? ? ?Knifey-Spoony數(shù)據(jù)集：含有刀子、叉子、湯匙，共計22M左右。Knifey-Spoony數(shù)據(jù)集由一個視頻文件取出幀并轉(zhuǎn)換成圖像產(chǎn)生。 訓練集包含4170幅圖像，測試集包含530幅圖像。?訓練集中只有994張叉子的圖像，卻包含著1201張刀子的圖像和1966張湯匙的圖像。

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##The Knifey-Spoony Data-Set

[Original repository on GitHub](https://github.com/Hvass-Labs/knifey-spoony)
Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)

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## Introduction

* This is the Knifey-Spoony image data-set.
* The images show 3 types of objects: Cutlery knives, spoons and forks on a few different backgrounds.
* The classes are named: knifey, spoony and forky. (It's a spoof from The Simpsons on the 1980's movie Crocodile Dundee.)
* These images are used in [TensorFlow Tutorial #09](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/08_Video_Data.ipynb) as an example of a classification problem.
* There is a [script](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/convert.py) for converting videos to images so you can easily create your own data-set with thousands of images from just a few video-recordings.

*這是Knifey-Spoony圖像數(shù)據(jù)集。
*圖片顯示了3種不同背景的物體：刀具、勺子和叉子。
*這些課程被命名為：刀叉，幽靈和叉子。（這是1980年代電影《The Simpsons》中辛普森一家的一個spoof。）
*這些圖像在[tensorflow tutorial_09]中（https://github.com/hvass-labs/tensorflow-tutorials/blob/master/08_video_data.ipynb）用作分類問題的示例。
*有一個[腳本]（https://github.com/hvass-labs/tensorflow-tutorials/blob/master/convert.py）用于將視頻轉(zhuǎn)換為圖像，這樣您就可以輕松地創(chuàng)建自己的數(shù)據(jù)集，其中包含僅幾段視頻記錄中的數(shù)千個圖像。

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## Images

* All images are 200 x 200 pixels with 3 colour channels.
* There is a total of 4700 jpg-images of which 530 are test-images with different backgrounds than the training-set.
* The knifey class has 1347 images total (137 images in the test-set).
* The spoony class has 2208 images total (242 images in the test-set).
* The forky class has 1145 images total (151 images in the test-set).

*所有圖像均為200 x 200像素，帶有3個彩色通道。
*總共有4700張JPG圖像，其中530張是測試圖像，其背景與訓練集不同。
*Knifey類總共有1347個圖像（測試集中有137個圖像）。
*Spoony類總共有2208個圖像（測試集中有242個圖像）。
*Forky類總共有1145個圖像（測試集中有151個圖像）。

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Knifey-Spoony數(shù)據(jù)集的下載

The archived tar-ball is automatically downloaded and extracted by using the [knifey.py](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/knifey.py) module for Python.

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Knifey-Spoony數(shù)據(jù)集的使用方法

DL之VGG16：基于VGG16(Keras)利用Knifey-Spoony數(shù)據(jù)集對網(wǎng)絡(luò)架構(gòu)FineTuning和遷移學習

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