import{S as Nt,i as Rt,s as Yt,e as n,k as h,w as k,t as s,M as zt,c as r,d as t,m as g,a as i,x as q,h as o,b as u,G as e,g as p,y as I,q as P,o as x,B as F,v as Ut}from"../chunks/vendor-hf-doc-builder.js";import{T as pt}from"../chunks/Tip-hf-doc-builder.js";import{I as ct}from"../chunks/IconCopyLink-hf-doc-builder.js";import{C as ra}from"../chunks/CodeBlock-hf-doc-builder.js";function Gt(Y){let d,E,m,$,v,f,b,w;return{c(){d=n("p"),E=s("To work with image datasets, you need to have the "),m=n("code"),$=s("vision"),v=s(" dependency installed. Check out the "),f=n("a"),b=s("installation"),w=s(" guide to learn how to install it."),this.h()},l(_){d=r(_,"P",{});var c=i(d);E=o(c,"To work with image datasets, you need to have the "),m=r(c,"CODE",{});var j=i(m);$=o(j,"vision"),j.forEach(t),v=o(c," dependency installed. Check out the "),f=r(c,"A",{href:!0});var C=i(f);b=o(C,"installation"),C.forEach(t),w=o(c," guide to learn how to install it."),c.forEach(t),this.h()},h(){u(f,"href","./installation#vision")},m(_,c){p(_,d,c),e(d,E),e(d,m),e(m,$),e(d,v),e(d,f),e(f,b),e(d,w)},d(_){_&&t(d)}}}function Ht(Y){let d,E,m,$,v,f,b,w;return{c(){d=n("p"),E=s("Index into an image dataset using the row index first and then the "),m=n("code"),$=s("image"),v=s(" column - "),f=n("code"),b=s('dataset[0]["image"]'),w=s(" - 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.")},l(_){d=r(_,"P",{});var c=i(d);E=o(c,"Index into an image dataset using the row index first and then the "),m=r(c,"CODE",{});var j=i(m);$=o(j,"image"),j.forEach(t),v=o(c," column - "),f=r(c,"CODE",{});var C=i(f);b=o(C,'dataset[0]["image"]'),C.forEach(t),w=o(c," - to avoid decoding and resampling all the image objects in the dataset. Otherwise, this can be a slow and time-consuming process if you have a large dataset."),c.forEach(t)},m(_,c){p(_,d,c),e(d,E),e(d,m),e(m,$),e(d,v),e(d,f),e(f,b),e(d,w)},d(_){_&&t(d)}}}function Mt(Y){let d,E,m,$,v,f,b,w;return{c(){d=n("p"),E=s("For more information about creating your own "),m=n("code"),$=s("ImageFolder"),v=s(" dataset, take a look at the "),f=n("a"),b=s("Create an image dataset"),w=s(" guide."),this.h()},l(_){d=r(_,"P",{});var c=i(d);E=o(c,"For more information about creating your own "),m=r(c,"CODE",{});var j=i(m);$=o(j,"ImageFolder"),j.forEach(t),v=o(c," dataset, take a look at the "),f=r(c,"A",{href:!0});var C=i(f);b=o(C,"Create an image dataset"),C.forEach(t),w=o(c," guide."),c.forEach(t),this.h()},h(){u(f,"href","./image_dataset")},m(_,c){p(_,d,c),e(d,E),e(d,m),e(m,$),e(d,v),e(d,f),e(f,b),e(d,w)},d(_){_&&t(d)}}}function Wt(Y){let d,E,m,$,v,f,b,w,_,c,j,C,va,ce,me,Ta,z,Na,A,fe,wa,he,ge,ia,ue,_e,Ra,Q,Ya,U,za,G,$e,V,ve,we,Ua,N,H,ja,X,je,Ea,Ee,Ga,L,be,da,ye,ke,pa,qe,Ie,Ha,Z,Ma,O,Pe,ba,xe,Fe,ca,Ce,De,Wa,aa,Ja,R,M,ya,ea,Ae,ka,Le,Ka,S,Oe,qa,Se,Be,Ia,Te,Ne,Qa,ta,Va,B,Re,Pa,Ye,ze,xa,Ue,Ge,Xa,sa,Za,W,He,Fa,Me,We,ae,oa,ee,y,Je,Ca,Ke,Qe,Da,Ve,Xe,ma,Ze,at,Aa,et,tt,te,D,st,La,ot,lt,fa,nt,rt,Oa,it,dt,se,la,oe,J,le;return f=new ct({}),z=new pt({props:{$$slots:{default:[Gt]},$$scope:{ctx:Y}}}),Q=new ra({props:{code:`from datasets import load_dataset, Image

dataset = load_dataset("beans", split="train")
dataset[0]["image"]`,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>]`}}),U=new pt({props:{warning:!0,$$slots:{default:[Ht]},$$scope:{ctx:Y}}}),X=new ct({}),Z=new ra({props:{code:`from datasets import load_dataset, Image

dataset = Dataset.from_dict({"image": ["path/to/image_1", "path/to/image_2", ..., "path/to/image_n"]}).cast_column("image", Image())
dataset[0]["image"]`,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 = 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;]`}}),aa=new ra({props:{code:`dataset = load_dataset("beans", split="train").cast_column("image", Image(decode=False))
dataset[0]["image"]`,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>}`}}),ea=new ct({}),ta=new ra({props:{code:`folder/train/dog/golden_retriever.png
folder/train/dog/german_shepherd.png
folder/train/dog/chihuahua.png

folder/train/cat/maine_coon.png
folder/train/cat/bengal.png
folder/train/cat/birman.png`,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`}}),sa=new ra({props:{code:`from datasets import load_dataset

dataset = load_dataset("imagefolder", data_dir="/path/to/folder")
dataset["train"][0]

dataset["train"][-1]`,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>}`}}),oa=new ra({props:{code:'dataset = load_dataset("imagefolder", data_files="https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip", split="train")',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_3367a.zip&quot;</span>, split=<span class="hljs-string">&quot;train&quot;</span>)'}}),la=new ra({props:{code:`from datasets import load_dataset

dataset = load_dataset("imagefolder", data_dir="/path/to/folder", drop_labels=False)`,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>)`}}),J=new pt({props:{$$slots:{default:[Mt]},$$scope:{ctx:Y}}}),{c(){d=n("meta"),E=h(),m=n("h1"),$=n("a"),v=n("span"),k(f.$$.fragment),b=h(),w=n("span"),_=s("Load image data"),c=h(),j=n("p"),C=s("Image datasets are loaded from the "),va=n("code"),ce=s("image"),me=s(" column, which contains a PIL object."),Ta=h(),k(z.$$.fragment),Na=h(),A=n("p"),fe=s("When you load an image dataset and call the "),wa=n("code"),he=s("image"),ge=s(" column, the "),ia=n("a"),ue=s("Image"),_e=s(" feature automatically decodes the PIL object into an image:"),Ra=h(),k(Q.$$.fragment),Ya=h(),k(U.$$.fragment),za=h(),G=n("p"),$e=s("For a guide on how to load any type of dataset, take a look at the "),V=n("a"),ve=s("general loading guide"),we=s("."),Ua=h(),N=n("h2"),H=n("a"),ja=n("span"),k(X.$$.fragment),je=h(),Ea=n("span"),Ee=s("Local files"),Ga=h(),L=n("p"),be=s("You can load a dataset from the image path. 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The metadata is automatically loaded when you call "),ma=n("a"),Ze=s("load_dataset()"),at=s(" and specify "),Aa=n("code"),et=s("imagefolder"),tt=s("."),te=h(),D=n("p"),st=s("To ignore the information in the metadata file, set "),La=n("code"),ot=s("drop_labels=False"),lt=s(" in "),fa=n("a"),nt=s("load_dataset()"),rt=s(", and allow "),Oa=n("code"),it=s("ImageFolder"),dt=s(" to automatically infer the label name from the directory name:"),se=h(),k(la.$$.fragment),oe=h(),k(J.$$.fragment),this.h()},l(a){const l=zt('[data-svelte="svelte-1phssyn"]',document.head);d=r(l,"META",{name:!0,content:!0}),l.forEach(t),E=g(a),m=r(a,"H1",{class:!0});var na=i(m);$=r(na,"A",{id:!0,class:!0,href:!0});var Sa=i($);v=r(Sa,"SPAN",{});var Ba=i(v);q(f.$$.fragment,Ba),Ba.forEach(t),Sa.forEach(t),b=g(na),w=r(na,"SPAN",{});var mt=i(w);_=o(mt,"Load image data"),mt.forEach(t),na.forEach(t),c=g(a),j=r(a,"P",{});var ne=i(j);C=o(ne,"Image datasets are loaded from the "),va=r(ne,"CODE",{});var ft=i(va);ce=o(ft,"image"),ft.forEach(t),me=o(ne," column, which contains a PIL object."),ne.forEach(t),Ta=g(a),q(z.$$.fragment,a),Na=g(a),A=r(a,"P",{});var ha=i(A);fe=o(ha,"When you load an image dataset and call the "),wa=r(ha,"CODE",{});var ht=i(wa);he=o(ht,"image"),ht.forEach(t),ge=o(ha," column, the "),ia=r(ha,"A",{href:!0});var gt=i(ia);ue=o(gt,"Image"),gt.forEach(t),_e=o(ha," feature automatically decodes the PIL object into an image:"),ha.forEach(t),Ra=g(a),q(Q.$$.fragment,a),Ya=g(a),q(U.$$.fragment,a),za=g(a),G=r(a,"P",{});var re=i(G);$e=o(re,"For a guide on how to load any type of dataset, take a look at the "),V=r(re,"A",{class:!0,href:!0});var ut=i(V);ve=o(ut,"general loading guide"),ut.forEach(t),we=o(re,"."),re.forEach(t),Ua=g(a),N=r(a,"H2",{class:!0});var ie=i(N);H=r(ie,"A",{id:!0,class:!0,href:!0});var _t=i(H);ja=r(_t,"SPAN",{});var $t=i(ja);q(X.$$.fragment,$t),$t.forEach(t),_t.forEach(t),je=g(ie),Ea=r(ie,"SPAN",{});var vt=i(Ea);Ee=o(vt,"Local files"),vt.forEach(t),ie.forEach(t),Ga=g(a),L=r(a,"P",{});var ga=i(L);be=o(ga,"You can load a dataset from the image path. 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