autotrain/pr_749/en/image_classification.html

<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Image Classification&quot;,&quot;local&quot;:&quot;image-classification&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Preparing your data&quot;,&quot;local&quot;:&quot;preparing-your-data&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Organizing Images&quot;,&quot;local&quot;:&quot;organizing-images&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3},{&quot;title&quot;:&quot;Image Requirements&quot;,&quot;local&quot;:&quot;image-requirements&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3}],&quot;depth&quot;:2}],&quot;depth&quot;:1}">
		<link href="/docs/autotrain/pr_749/en/_app/immutable/assets/0.e3b0c442.css" rel="modulepreload">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/entry/start.b4f8a0ef.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/scheduler.0219f8bd.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/singletons.74a96c49.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/paths.5815e531.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/entry/app.4f18d4a0.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/index.f61edf3b.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/nodes/0.3ba41ccf.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/nodes/11.806dcf2c.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/CodeBlock.38e566ae.js">
		<link rel="modulepreload" href="/docs/autotrain/pr_749/en/_app/immutable/chunks/EditOnGithub.48fa589f.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;Image Classification&quot;,&quot;local&quot;:&quot;image-classification&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Preparing your data&quot;,&quot;local&quot;:&quot;preparing-your-data&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Organizing Images&quot;,&quot;local&quot;:&quot;organizing-images&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3},{&quot;title&quot;:&quot;Image Requirements&quot;,&quot;local&quot;:&quot;image-requirements&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3}],&quot;depth&quot;:2}],&quot;depth&quot;:1}"><!-- HEAD_svelte-u9bgzb_END -->      <p></p>  <h1 class="relative group"><a id="image-classification" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#image-classification"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Image Classification</span></h1> <p data-svelte-h="svelte-xe07dq">Image classification is a form of supervised learning where a model is trained to identify
and categorize objects within images. AutoTrain simplifies the process, enabling you to
train a state-of-the-art image classification model by simply uploading labeled example
images.</p>  <h2 class="relative group"><a id="preparing-your-data" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#preparing-your-data"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Preparing your data</span></h2> <p data-svelte-h="svelte-li8p8w">To ensure your image classification model trains effectively, follow these guidelines for preparing your data:</p>  <h3 class="relative group"><a id="organizing-images" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#organizing-images"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Organizing Images</span></h3> <p data-svelte-h="svelte-14s5g1n">Prepare a zip file containing your categorized images. Each category should have its own
subfolder named after the class it represents. For example, to differentiate between
‘cats’ and ‘dogs’, your zip file structure should resemble the following:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->cats_and_dogs<span class="hljs-selector-class">.zip</span>
├── cats
│   ├── cat.<span class="hljs-number">1</span><span class="hljs-selector-class">.jpg</span>
│   ├── cat.<span class="hljs-number">2</span><span class="hljs-selector-class">.jpg</span>
│   ├── cat.<span class="hljs-number">3</span><span class="hljs-selector-class">.jpg</span>
│   └── ...
└── dogs
    ├── dog.<span class="hljs-number">1</span><span class="hljs-selector-class">.jpg</span>
    ├── dog.<span class="hljs-number">2</span><span class="hljs-selector-class">.jpg</span>
    ├── dog.<span class="hljs-number">3</span><span class="hljs-selector-class">.jpg</span>
    └── ...<!-- HTML_TAG_END --></pre></div>  <h3 class="relative group"><a id="image-requirements" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#image-requirements"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Image Requirements</span></h3> <ul data-svelte-h="svelte-1jor5en"><li><p>Format: Ensure all images are in JPEG, JPG, or PNG format.</p></li> <li><p>Quantity: Include at least 5 images per class to provide the model with sufficient examples for learning.</p></li> <li><p>Exclusivity: The zip file should exclusively contain folders named after the classes,
and these folders should only contain relevant images. No additional files or nested
folders should be included.</p></li></ul> <p data-svelte-h="svelte-e9l10u"><strong>Additional Tips</strong></p> <ul data-svelte-h="svelte-8iu1fq"><li><p>Uniformity: While not required, having images of similar sizes and resolutions can help improve model performance.</p></li> <li><p>Variability: Include a variety of images for each class to encompass the range of
appearances and contexts the model might encounter in real-world scenarios.</p></li></ul> <p data-svelte-h="svelte-ddxna6">Some points to keep in mind:</p> <ul data-svelte-h="svelte-wgwixf"><li>The zip file should contain multiple folders (the classes), each folder should contain images of a single class.</li> <li>The name of the folder should be the name of the class.</li> <li>The images must be jpeg, jpg or png.</li> <li>There should be at least 5 images per class.</li> <li>There must not be any other files in the zip file.</li> <li>There must not be any other folders inside the zip folder.</li></ul> <p data-svelte-h="svelte-tredq4">When train.zip is decompressed, it creates two folders: cats and dogs. these are the two categories for classification. The images for both categories are in their respective folders. You can have as many categories as you want.</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/autotrain-advanced/blob/main/docs/source/image_classification.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1">&lt;</span> <span data-svelte-h="svelte-x0xyl0">&gt;</span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a>  <p></p> 
			
			<script>
				{
					__sveltekit_ewvlbq = {
						assets: "/docs/autotrain/pr_749/en",
						base: "/docs/autotrain/pr_749/en",
						env: {}
					};

					const element = document.currentScript.parentElement;

					const data = [null,null];

					Promise.all([
						import("/docs/autotrain/pr_749/en/_app/immutable/entry/start.b4f8a0ef.js"),
						import("/docs/autotrain/pr_749/en/_app/immutable/entry/app.4f18d4a0.js")
					]).then(([kit, app]) => {
						kit.start(app, element, {
							node_ids: [0, 11],
							data,
							form: null,
							error: null
						});
					});
				}
			</script>