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I Tested 4 Python OCR Libraries on the Same Invoice

December 2025. PaddleOCR, Tesseract, EasyOCR, GPT-4o. Real test.

Most OCR comparison articles are marketing fluff. I ran all four libraries on the same invoice and measured everything.

The Results

Library Time Confidence Errors Cost
PaddleOCR 4.85s 99.6% 0 $0
Tesseract 5.5 0.77s 91.1% 3 $0
EasyOCR 0.59s 80.8% 7 $0
GPT-4o 7.58s N/A 0 ~$0.01
Sample invoice used for OCR testing

The test invoice. 800x600 pixels, clean scan.

The Errors

Not all errors are equal. Here's what each library got wrong:

Tesseract (3 errors)

  • "Qty" became "ay"
  • "UI/UX Design" became "UWUX Design"
  • "Tax (8.5%):" lost the colon

EasyOCR (7 errors)

  • "$150.00" became "8150.00"
  • "$125.00" became "8125.00"
  • "$2,500.00" became "82,500.00"
  • "$8,980.00" became "88,980.00"
  • "$763.30" became "8763.30"
  • Confused $ with 8 throughout the document

EasyOCR's dollar sign confusion is systematic - it would break any invoice parser. Tesseract's errors are more random but could still cause validation failures.

Visual Comparison: Bounding Boxes

Here's how each algorithm detects text regions. The boxes show what each engine "sees":

Bounding box comparison showing how PaddleOCR, Tesseract, and EasyOCR detect text regions

Top-left: Original. Top-right: PaddleOCR (green, 29 boxes). Bottom-left: Tesseract (blue, 47 boxes). Bottom-right: EasyOCR (orange, 28 boxes).

Notice how Tesseract fragments text into many small boxes (47 vs 29), which is why it's faster but less accurate - it's doing less work to understand text groupings. PaddleOCR and EasyOCR both detect logical text blocks, but PaddleOCR has consistently higher confidence (99-100% vs 71-100%).

My Recommendation

Use PaddleOCR.

It's the only free option that got everything right. Yes, it's slower (4.85s vs 0.59s for EasyOCR), but what good is speed if your numbers are wrong?

GPT-4o also got perfect accuracy and preserved the table structure, but costs ~$0.01/image. Use it when you need document understanding, not just text extraction.

When to Use Each

PaddleOCR
When accuracy matters. Financial documents. Data validation. The default choice.
Tesseract
When speed matters more than accuracy. Search indexing. Resource-constrained systems.
EasyOCR
Avoid for documents with numbers/currency. OK for pure text like book pages.
GPT-4o
When you need document understanding. Tables. Complex layouts. Small batches.

The Code

PaddleOCR

from paddleocr import PaddleOCR

ocr = PaddleOCR(lang='en')
result = ocr.predict('invoice.png')

for item in result:
    for text in item.get('rec_texts', []):
        print(text)

Install: pip install paddleocr paddlepaddle

Tesseract

import pytesseract
from PIL import Image

image = Image.open('invoice.png')
text = pytesseract.image_to_string(image)
print(text)

Install: brew install tesseract && pip install pytesseract pillow

EasyOCR

import easyocr

reader = easyocr.Reader(['en'])
result = reader.readtext('invoice.png')

for bbox, text, conf in result:
    print(text)

Install: pip install easyocr

GPT-4o

import base64
from openai import OpenAI

client = OpenAI()

with open('invoice.png', 'rb') as f:
    img = base64.b64encode(f.read()).decode()

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": [
        {"type": "text", "text": "Extract all text from this image."},
        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{img}"}}
    ]}]
)

print(response.choices[0].message.content)

Install: pip install openai

Bottom Line

Start with PaddleOCR. It's free, accurate, and handles most cases. When you need document understanding (tables, Q&A), use GPT-4o on specific documents.

Tesseract is still useful for speed-critical applications where you can tolerate errors. EasyOCR has too many systematic issues with numbers to recommend for invoices or financial documents.

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