Pull the text out of any image with OCR. Runs entirely in your browser — the file never leaves your device.
Drop an image here, or click to choose
PNG, JPG, WEBP or GIF
Optical character recognition turns the pixels of a photo or scan back into characters you can select, search and edit. Going from picture to text takes a few seconds in this online image to text converter, and the whole process is below.
Drag a file onto the upload area, click to browse your device, or paste a direct image URL. PNG, JPG, WEBP and GIF are all supported, and screenshots work just as well as photos.
Press Extract text. The OCR engine loads in your browser and reads the image locally — the progress bar tracks it as it works through the page.
The recognised text appears below with a word and character count. Copy it to your clipboard in one click, or download it as a .txt file named after your image.
Anywhere text is trapped inside an image, this converter gets it back out.
Turn a scanned contract, form or letter back into text you can search and edit.
Lift text out of a screenshot when copying from the original window is not possible.
Pull totals, dates and reference numbers out of a photographed receipt for your records.
Photograph a page and convert the passage into text you can quote or translate.
Capture a lecture slide or meeting whiteboard and keep the notes as editable text.
Read serial numbers, product labels or signage from a photo without typing them out.
Turn a photographed card into text you can paste straight into your contacts instead of retyping a name, number and address by hand.
Looking for an image to text translator? Convert the picture to text here first, then paste the result into the translator of your choice. Translation tools work far better on clean text than on a photo.
Optical character recognition is reliable in some situations and genuinely poor in others. Knowing which is which saves you from retyping a page you assumed the software would handle.
This gets searched for under half a dozen labels. An image to text converter, a picture to text converter, an OCR image to text tool, an image to text generator, a free image to text converter — every one describes the same operation: reading the writing inside a picture and handing back characters you can edit.
Which words someone reaches for usually depends on what they are holding. People with a scan tend to say convert image to text. People with a photo on their phone tend to say convert picture to text. A few search for how to convert text in image to text, which is the same request phrased more literally. The tool behaves identically whichever description brought you here.
An image file holds nothing but colour values. There is no letter "A" stored anywhere in a photograph of a page — only a pattern of dark pixels that a human eye resolves into a shape it recognises. OCR is the process of doing that recognition in software.
The engine first separates the writing from the background, then finds the lines, then the individual characters within each line, and finally matches each shape against a trained model of what letters look like. That is why the phrase people search for varies so much: image to text, picture to text, and convert image to text all describe the same underlying job.
Newer image to text AI models have pushed accuracy well past the template matching that older software relied on, particularly on unusual fonts and low-contrast scans. The engine used here runs that model on your own device rather than on a server.
Because it is a recognition problem rather than a lookup, the output is a best guess. A clean scan produces a guess that is right essentially every time. A blurred photo of a curved page under a desk lamp produces a guess that needs proofreading.
The engine ships with trained data for over a hundred languages, including Arabic, Chinese, Japanese, Korean, Hindi, Russian and the full Latin-script European set. Accuracy is highest for languages written in the Latin alphabet simply because those models have been trained on the most material.
Mixing scripts on one page — an English caption under Japanese text, for example — usually works, but the minority script tends to lose accuracy. If a document is genuinely bilingual and both halves matter, running it twice and keeping the better half of each pass is more reliable than one combined attempt.
Printed type is a solved problem. Handwriting is not, and no browser-based OCR handles it well. Neat block capitals sometimes come through; ordinary cursive rarely does, and the failure is often silent — you get plausible-looking words that are not the ones on the page.
If the result from a handwritten note looks convincing, read it against the original before trusting it. That is the one case where OCR can cost you more time than typing would have.
A flatbed scan is the ideal input: even lighting, no perspective distortion, high resolution. A screenshot is nearly as good, since the text was rendered digitally and the pixels are sharp.
A phone photograph is the hardest of the three. The page curves, the lighting is uneven, and the camera is rarely square to the paper. Flattening the page, turning on more light and shooting straight down makes a larger difference to the result than any setting in the tool.
For a scanned PDF rather than an image, convert the pages with the PDF to JPG tool first, then run the images through here.
Most online converters upload your file, process it on a server and send the text back. That means a document you may not want to share — a contract, a payslip, a medical letter — sits on someone else's machine for an unknown length of time.
This tool loads the recognition engine into the page instead, so the image is read on your own device and no copy is ever transmitted. The practical consequence is that it also works with no connection once the page has loaded, and there is no upload wait on a large file.
OCR accuracy depends almost entirely on the quality of the image you feed it. A few small changes before you upload make a large difference to the output.
How the OCR works and what to expect from it.
Upload the image, press Extract text, and the OCR engine reads it locally in your browser. The recognized text appears underneath with a word count, ready to copy or download as a .txt file. Nothing is sent to a server at any point.
Other things you can do here without signing up.