How do I get OCR text from JPG and PNG images through an API?

You can get OCR text from JPG and PNG images by sending the image to an OCR API and reading the extracted text from the response.

Typical flow

1. Choose an OCR API
   Common options: Google Cloud Vision, AWS Textract, Azure AI Vision, OCR.space, Mindee, etc.

2. Send the image

   • JPG/PNG file upload via multipart/form-data, or
   • Base64-encoded image in JSON, or
   • Public image URL

3. Read the OCR result The API usually returns:

   • plain extracted text
   • detected language
   • bounding boxes / positions
   • confidence scores

Example: OCR.space API

cURL

curl -X POST "https://api.ocr.space/parse/image" \
  -H "apikey: YOUR_API_KEY" \
  -F "file=@image.jpg"

Python

import requests

url = "https://api.ocr.space/parse/image"
payload = {'apikey': 'YOUR_API_KEY'}
files = {'file': open('image.png', 'rb')}

response = requests.post(url, data=payload, files=files)
print(response.json()["ParsedResults"][0]["ParsedText"])

Example: Google Cloud Vision API

You typically send the image content in base64:

import base64
import requests

with open("image.jpg", "rb") as f:
    img_b64 = base64.b64encode(f.read()).decode()

url = "https://vision.googleapis.com/v1/images:annotate?key=YOUR_API_KEY"
data = {
    "requests": [
        {
            "image": {"content": img_b64},
            "features": [{"type": "TEXT_DETECTION"}]
        }
    ]
}

resp = requests.post(url, json=data)
print(resp.json()["responses"][0]["fullTextAnnotation"]["text"])

Notes

• JPG and PNG are both commonly supported.
• If the image is large or low quality, OCR accuracy may drop.
• Some APIs work best with:
  • straightened text
  • high contrast
  • minimal blur
  • good resolution

If you want, I can give you a working example for a specific API in Python, JavaScript, or cURL.