Upload a clear image and extract visible information into practical JSON for spreadsheets, databases, QA review, LLM workflows, and automation. The response includes extracted data, a suggested schema, and review notes so you can spot uncertain values before using it downstream.
Best for OCR text, table rows, form fields, receipts, invoices, answer sheets, UI screenshots, product details, and scene data. This extracts readable or visible information into JSON; it does not encode the image file as Base64.
Use a sharp JPG, PNG, or WebP where text, rows, labels, totals, selected answers, UI copy, or product details are readable. Crop to the part you want extracted for cleaner JSON.
Max file size: 5MB max
JSON mode
Generated JSON
Review generated JSON before using it in automation. Low-quality images, partial screenshots, handwriting, and cropped rows can require manual correction.
Use a clear image, choose the extraction focus, then review structured JSON before sending it to a spreadsheet, database, LLM workflow, or automation.
Add a screenshot, receipt, invoice, form, table, answer sheet, product photo, or other image where the important information is visible.
Use Auto JSON for general extraction, OCR/Text for readable text, Table/Form for rows and fields, or Scene JSON for visible objects and context.
Get extracted data as JSON objects or arrays, with schema guidance when the image suggests a repeatable structure.
Check notes for uncertain values, cropped areas, blurry text, or ambiguous labels, then copy the full response or data only.
Use it when you need structured data from visible image content, not just a plain OCR transcript or a Base64-encoded image file.
Convert receipt OCR to JSON, invoice image to JSON, form OCR to JSON, table image to JSON, screenshot data to JSON, or product details into practical objects and arrays.
Add notes when you need specific keys, nested objects, line_items arrays, null values for missing fields, preserved table headers, or only selected answers.
Use the notes to catch blurry text, cropped fields, ambiguous labels, handwriting issues, or values that need manual checking before the JSON goes into another system.
Answers to common questions about OCR, structured extraction, Base64 confusion, custom fields, and image quality.
On this page, image to JSON means extracting useful visible information from an image and returning it as structured JSON objects or arrays. It can read text, rows, fields, answers, totals, labels, product details, UI content, or scene details depending on the image and selected mode.
It includes OCR, but it is not limited to plain text extraction. OCR/Text mode focuses on visible text, while Table/Form mode can organize rows, fields, receipts, forms, and answer sheets into arrays or key-value objects. Auto mode chooses the most useful structure for the image.
Yes. Upload a clear receipt, invoice, form, worksheet, answer sheet, screenshot, or table image and use Auto JSON or Table/Form mode. The result can include structured fields such as line items, labels, selected answers, dates, prices, totals, rows, columns, and notes about anything uncertain.
No. This tool extracts information from the image into JSON. If you need to store the image bytes inside a JSON file, that is usually done with Base64 encoding, which is a different developer workflow and not the purpose of this converter.
Yes. Use the optional extraction notes to request fields, arrays, naming patterns, or focus areas. For example, ask for line_items as an array, preserve blank form fields as null, extract only selected answers, or use keys such as vendor, subtotal, tax, and total.
Yes. Add extraction notes with the exact keys, arrays, nested objects, null handling, or naming style you want. For repeatable workflows, describe the target schema clearly before generating and review the output before sending it to another system.
Table/Form mode is designed to preserve visible rows, columns, labels, and headers when the image is clear. For best results, crop to the table area, keep headers fully visible, and avoid blurry or low-contrast screenshots.
Accuracy depends on image quality, crop, layout complexity, handwriting, glare, blur, and whether important values are visible. Review the generated JSON before using it in automation. The notes field is designed to flag uncertain text, cropped content, or places that may need manual correction.
Sharp images with readable text and a focused crop work best. Use JPG, PNG, or WebP under the upload limit, avoid heavy compression, and crop out unrelated areas when you only need one table, form section, receipt, or screenshot panel extracted.
Upload a screenshot, table, form, receipt, invoice, answer sheet, or product photo and get JSON with extracted data, schema guidance, and review notes.