import{s as Bt,o as Pt,n as Rt}from"../chunks/scheduler.bdbef820.js";import{S as Vt,i as Qt,g as p,s as n,r as m,A as Dt,h as d,f as e,c as i,j as zt,u as r,x as u,k as Et,y as St,a as s,v as g,d as c,t as h,w as f}from"../chunks/index.c0aea24a.js";import{T as _t}from"../chunks/Tip.31005f7d.js";import{C as j}from"../chunks/CodeBlock.6ccca92e.js";import{H as Ut,E as At}from"../chunks/EditOnGithub.725ee0c1.js";function Kt(y){let l,$='To work with image datasets, you need to have the <code>vision</code> dependency installed. Check out the <a href="./installation#vision">installation</a> guide to learn how to install it.';return{c(){l=p("p"),l.innerHTML=$},l(o){l=d(o,"P",{"data-svelte-h":!0}),u(l)!=="svelte-p8ou1r"&&(l.innerHTML=$)},m(o,J){s(o,l,J)},p:Rt,d(o){o&&e(l)}}}function Ot(y){let l,$="Index into an image dataset using the row index first and then the <code>image</code> column - <code>dataset[0][&quot;image&quot;]</code> - to avoid decoding and resampling all the image objects in the dataset. Otherwise, this can be a slow and time-consuming process if you have a large dataset.";return{c(){l=p("p"),l.innerHTML=$},l(o){l=d(o,"P",{"data-svelte-h":!0}),u(l)!=="svelte-1qc6mpf"&&(l.innerHTML=$)},m(o,J){s(o,l,J)},p:Rt,d(o){o&&e(l)}}}function ta(y){let l,$='For more information about creating your own <code>ImageFolder</code> dataset, take a look at the <a href="./image_dataset">Create an image dataset</a> guide.';return{c(){l=p("p"),l.innerHTML=$},l(o){l=d(o,"P",{"data-svelte-h":!0}),u(l)!=="svelte-1nxblik"&&(l.innerHTML=$)},m(o,J){s(o,l,J)},p:Rt,d(o){o&&e(l)}}}function aa(y){let l,$,o,J,w,S,U,Zt='Image datasets have <a href="/docs/datasets/v3.0.0/en/package_reference/main_classes#datasets.Image">Image</a> type columns, which contain PIL objects.',A,b,K,_,Gt="When you load an image dataset and call the image column, the images are decoded as PIL Images:",O,R,tt,M,at,Z,It='For a guide on how to load any type of dataset, take a look at the <a class="underline decoration-sky-400 decoration-2 font-semibold" href="./loading">general loading guide</a>.',et,G,st,I,kt='You can load a dataset from the image path. Use the <a href="/docs/datasets/v3.0.0/en/package_reference/main_classes#datasets.Dataset.cast_column">cast_column()</a> function to accept a column of image file paths, and decode it into a PIL image with the <a href="/docs/datasets/v3.0.0/en/package_reference/main_classes#datasets.Image">Image</a> feature:',lt,k,nt,v,vt='If you only want to load the underlying path to the image dataset without decoding the image object, set <code>decode=False</code> in the <a href="/docs/datasets/v3.0.0/en/package_reference/main_classes#datasets.Image">Image</a> feature:',it,F,ot,C,pt,q,Ft="You can also load a dataset with an <code>ImageFolder</code> dataset builder which does not require writing a custom dataloader. This makes <code>ImageFolder</code> ideal for quickly creating and loading image datasets with several thousand images for different vision tasks. Your image dataset structure should look like this:",dt,x,mt,W,Ct="Load your dataset by specifying <code>imagefolder</code> and the directory of your dataset in <code>data_dir</code>:",rt,Y,gt,L,qt="Load remote datasets from their URLs with the <code>data_files</code> parameter:",ct,X,ht,N,xt='Some datasets have a metadata file (<code>metadata.csv</code>/<code>metadata.jsonl</code>) associated with it, containing other information about the data like bounding boxes, text captions, and labels. The metadata is automatically loaded when you call <a href="/docs/datasets/v3.0.0/en/package_reference/loading_methods#datasets.load_dataset">load_dataset()</a> and specify <code>imagefolder</code>.',ft,H,Wt='To ignore the information in the metadata file, set <code>drop_labels=False</code> in <a href="/docs/datasets/v3.0.0/en/package_reference/loading_methods#datasets.load_dataset">load_dataset()</a>, and allow <code>ImageFolder</code> to automatically infer the label name from the directory name:',ut,z,$t,T,Jt,E,yt,B,Yt=`The <a href="https://github.com/webdataset/webdataset" rel="nofollow">WebDataset</a> format is based on a folder of TAR archives and is suitable for big image datasets.
Because of their size, WebDatasets are generally loaded in streaming mode (using <code>streaming=True</code>).`,bt,P,Lt="You can load a WebDataset like this:",Mt,V,Tt,Q,jt,D,wt;return w=new Ut({props:{title:"Load image data",local:"load-image-data",headingTag:"h1"}}),b=new _t({props:{$$slots:{default:[Kt]},$$scope:{ctx:y}}}),R=new j({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTJDJTIwSW1hZ2UlMEElMEFkYXRhc2V0JTIwJTNEJTIwbG9hZF9kYXRhc2V0KCUyMmJlYW5zJTIyJTJDJTIwc3BsaXQlM0QlMjJ0cmFpbiUyMiklMEFkYXRhc2V0JTVCMCU1RCU1QiUyMmltYWdlJTIyJTVE",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset, Image

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;beans&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;image&quot;</span>]`,wrap:!1}}),M=new _t({props:{warning:!0,$$slots:{default:[Ot]},$$scope:{ctx:y}}}),G=new Ut({props:{title:"Local files",local:"local-files",headingTag:"h2"}}),k=new j({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwRGF0YXNldCUyQyUyMEltYWdlJTBBJTBBZGF0YXNldCUyMCUzRCUyMERhdGFzZXQuZnJvbV9kaWN0KCU3QiUyMmltYWdlJTIyJTNBJTIwJTVCJTIycGF0aCUyRnRvJTJGaW1hZ2VfMSUyMiUyQyUyMCUyMnBhdGglMkZ0byUyRmltYWdlXzIlMjIlMkMlMjAuLi4lMkMlMjAlMjJwYXRoJTJGdG8lMkZpbWFnZV9uJTIyJTVEJTdEKS5jYXN0X2NvbHVtbiglMjJpbWFnZSUyMiUyQyUyMEltYWdlKCkpJTBBZGF0YXNldCU1QjAlNUQlNUIlMjJpbWFnZSUyMiU1RA==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> Dataset, Image

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = Dataset.from_dict({<span class="hljs-string">&quot;image&quot;</span>: [<span class="hljs-string">&quot;path/to/image_1&quot;</span>, <span class="hljs-string">&quot;path/to/image_2&quot;</span>, ..., <span class="hljs-string">&quot;path/to/image_n&quot;</span>]}).cast_column(<span class="hljs-string">&quot;image&quot;</span>, Image())
<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;image&quot;</span>]
&lt;PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x215 at <span class="hljs-number">0x15E6D7160</span>&gt;]`,wrap:!1}}),F=new j({props:{code:"ZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJiZWFucyUyMiUyQyUyMHNwbGl0JTNEJTIydHJhaW4lMjIpLmNhc3RfY29sdW1uKCUyMmltYWdlJTIyJTJDJTIwSW1hZ2UoZGVjb2RlJTNERmFsc2UpKSUwQWRhdGFzZXQlNUIwJTVEJTVCJTIyaW1hZ2UlMjIlNUQ=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;beans&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>).cast_column(<span class="hljs-string">&quot;image&quot;</span>, Image(decode=<span class="hljs-literal">False</span>))
<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-number">0</span>][<span class="hljs-string">&quot;image&quot;</span>]
{<span class="hljs-string">&#x27;bytes&#x27;</span>: <span class="hljs-literal">None</span>,
 <span class="hljs-string">&#x27;path&#x27;</span>: <span class="hljs-string">&#x27;/root/.cache/huggingface/datasets/downloads/extracted/b0a21163f78769a2cf11f58dfc767fb458fc7cea5c05dccc0144a2c0f0bc1292/train/bean_rust/bean_rust_train.29.jpg&#x27;</span>}`,wrap:!1}}),C=new Ut({props:{title:"ImageFolder",local:"imagefolder",headingTag:"h2"}}),x=new j({props:{code:"Zm9sZGVyJTJGdHJhaW4lMkZkb2clMkZnb2xkZW5fcmV0cmlldmVyLnBuZyUwQWZvbGRlciUyRnRyYWluJTJGZG9nJTJGZ2VybWFuX3NoZXBoZXJkLnBuZyUwQWZvbGRlciUyRnRyYWluJTJGZG9nJTJGY2hpaHVhaHVhLnBuZyUwQSUwQWZvbGRlciUyRnRyYWluJTJGY2F0JTJGbWFpbmVfY29vbi5wbmclMEFmb2xkZXIlMkZ0cmFpbiUyRmNhdCUyRmJlbmdhbC5wbmclMEFmb2xkZXIlMkZ0cmFpbiUyRmNhdCUyRmJpcm1hbi5wbmc=",highlighted:`folder<span class="hljs-regexp">/train/</span>dog/golden_retriever.png
folder<span class="hljs-regexp">/train/</span>dog/german_shepherd.png
folder<span class="hljs-regexp">/train/</span>dog/chihuahua.png

folder<span class="hljs-regexp">/train/</span>cat/maine_coon.png
folder<span class="hljs-regexp">/train/</span>cat/bengal.png
folder<span class="hljs-regexp">/train/</span>cat/birman.png`,wrap:!1}}),Y=new j({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJpbWFnZWZvbGRlciUyMiUyQyUyMGRhdGFfZGlyJTNEJTIyJTJGcGF0aCUyRnRvJTJGZm9sZGVyJTIyKSUwQWRhdGFzZXQlNUIlMjJ0cmFpbiUyMiU1RCU1QjAlNUQlMEElMEFkYXRhc2V0JTVCJTIydHJhaW4lMjIlNUQlNUItMSU1RA==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;imagefolder&quot;</span>, data_dir=<span class="hljs-string">&quot;/path/to/folder&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-string">&quot;train&quot;</span>][<span class="hljs-number">0</span>]
{<span class="hljs-string">&quot;image&quot;</span>: &lt;PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x215 at <span class="hljs-number">0x15E6D7160</span>&gt;, <span class="hljs-string">&quot;label&quot;</span>: <span class="hljs-number">0</span>}

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset[<span class="hljs-string">&quot;train&quot;</span>][-<span class="hljs-number">1</span>]
{<span class="hljs-string">&quot;image&quot;</span>: &lt;PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1200x215 at <span class="hljs-number">0x15E8DAD30</span>&gt;, <span class="hljs-string">&quot;label&quot;</span>: <span class="hljs-number">1</span>}`,wrap:!1}}),X=new j({props:{code:"ZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJpbWFnZWZvbGRlciUyMiUyQyUyMGRhdGFfZmlsZXMlM0QlMjJodHRwcyUzQSUyRiUyRmRvd25sb2FkLm1pY3Jvc29mdC5jb20lMkZkb3dubG9hZCUyRjMlMkZFJTJGMSUyRjNFMUMzRjIxLUVDREItNDg2OS04MzY4LTZERUJBNzdCOTE5RiUyRmthZ2dsZWNhdHNhbmRkb2dzXzUzNDAuemlwJTIyJTJDJTIwc3BsaXQlM0QlMjJ0cmFpbiUyMik=",highlighted:'<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;imagefolder&quot;</span>, data_files=<span class="hljs-string">&quot;https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_5340.zip&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)',wrap:!1}}),z=new j({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJpbWFnZWZvbGRlciUyMiUyQyUyMGRhdGFfZGlyJTNEJTIyJTJGcGF0aCUyRnRvJTJGZm9sZGVyJTIyJTJDJTIwZHJvcF9sYWJlbHMlM0RGYWxzZSk=",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;imagefolder&quot;</span>, data_dir=<span class="hljs-string">&quot;/path/to/folder&quot;</span>, drop_labels=<span class="hljs-literal">False</span>)`,wrap:!1}}),T=new _t({props:{$$slots:{default:[ta]},$$scope:{ctx:y}}}),E=new Ut({props:{title:"WebDataset",local:"webdataset",headingTag:"h2"}}),V=new j({props:{code:"ZnJvbSUyMGRhdGFzZXRzJTIwaW1wb3J0JTIwbG9hZF9kYXRhc2V0JTBBJTBBZGF0YXNldCUyMCUzRCUyMGxvYWRfZGF0YXNldCglMjJ3ZWJkYXRhc2V0JTIyJTJDJTIwZGF0YV9kaXIlM0QlMjIlMkZwYXRoJTJGdG8lMkZmb2xkZXIlMjIlMkMlMjBzdHJlYW1pbmclM0RUcnVlKQ==",highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_dataset

<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_dataset(<span class="hljs-string">&quot;webdataset&quot;</span>, data_dir=<span class="hljs-string">&quot;/path/to/folder&quot;</span>, streaming=<span class="hljs-literal">True</span>)`,wrap:!1}}),Q=new 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ea='{"title":"Load image data","local":"load-image-data","sections":[{"title":"Local files","local":"local-files","sections":[],"depth":2},{"title":"ImageFolder","local":"imagefolder","sections":[],"depth":2},{"title":"WebDataset","local":"webdataset","sections":[],"depth":2}],"depth":1}';function sa(y){return Pt(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class da extends Vt{constructor(l){super(),Qt(this,l,sa,aa,Bt,{})}}export{da as component};
