OCR — Wyodrębnij tekst z obrazów

# OCR on a local image file
curl -X POST https://api.parsejet.com/v1/parse/auto/file \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "[email protected]"

# OCR on an image URL
curl -X POST https://api.parsejet.com/v1/parse/auto/url \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com/photo.jpg"}'

import httpx

# Extract text from an image using OCR
resp = httpx.post(
    "https://api.parsejet.com/v1/parse/auto/file",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    files={"file": open("screenshot.png", "rb")},
)
ocr_text = resp.json()["text"]
print(ocr_text)

# Batch OCR: process multiple images
from pathlib import Path

for img in Path("scans/").glob("*.jpg"):
    with open(img, "rb") as f:
        resp = httpx.post(
            "https://api.parsejet.com/v1/parse/auto/file",
            headers={"Authorization": "Bearer YOUR_API_KEY"},
            files={"file": (img.name, f, "image/jpeg")},
        )
    print(f"{img.name}: {resp.json()['text'][:100]}...")

// OCR on a file input from a web form
const fileInput = document.querySelector('input[type="file"]');
const file = fileInput.files[0];

const formData = new FormData();
formData.append("file", file);

const res = await fetch("https://api.parsejet.com/v1/parse/auto/file", {
  method: "POST",
  headers: { Authorization: "Bearer YOUR_API_KEY" },
  body: formData,
});
const { text } = await res.json();
console.log(text);  // Extracted text from image