German Umlauts Not Detected (Ä, Ö, Ü) in PaddleOCR

[sayinmehmet47]

Hi everyone,

I have implemented PaddleOCR to extract text from insurance cards. However, I noticed that some German umlauts (e.g., Ä, Ö, Ü) are not being correctly detected. I also updated the version of paddle ocr to latest , it also did not worked

For example, the word "EUROPÄISCHE" is recognized as "EUROPAISCHE", missing the Ä. Dömer detected as Domer

How can I improve the OCR model to correctly recognize German umlauts? Do I need to fine-tune the model, or is there a configuration I can adjust?

To help debug, I created a dedicated repository showing how I implemented OCR:

https://github.com/sayinmehmet47/ocr

I also have a testable endpoint available:

Any suggestions or guidance would be greatly appreciated!

Thanks in advance!

[GreatV]

It looks like PaddleOCR is not recognizing German umlauts (Ä, Ö, Ü) correctly in your use case. Here are a few steps you can take to improve the model's accuracy for German characters:

1. Check the Language Model Configuration

PaddleOCR uses different pre-trained models for different languages. Ensure that you are using a model that supports German characters. You can try using the multilingual model (ppocr_v3) or explicitly specify the German character set.

Modify the ocr_config to include a custom character list that includes umlauts:

custom_dict = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzÄÖÜäöüß"

You may also need to provide this dictionary in the configuration when initializing PaddleOCR.

2. Use a Custom Character List

If the default model does not properly recognize umlauts, you can modify the dict.txt file used during training. In PaddleOCR, changing the character dictionary can help the model recognize additional characters.

3. Try a Different Pre-trained Model

Some models may have better support for different languages. You could try initializing the OCR system with a different trained model and see if recognition improves:

ocr = PaddleOCR(lang="de")

If lang="de" isn't available, try using "en" or "multi" and customize the dictionary.

4. Fine-tune the Model

If the pre-trained models do not correctly recognize umlauts, fine-tuning the OCR model on a dataset that includes German text with umlauts could improve performance. You would need to:

• Collect images with German text containing umlauts.
• Annotate them correctly.
• Fine-tune a PaddleOCR model using those samples.

5. Preprocessing the Image

If the umlauts are not detected, try enhancing the image quality:

• Convert images to grayscale
• Increase contrast
• Apply adaptive thresholding
• Experiment with different resolutions

6. Post-processing Correction

You can use a dictionary-based correction approach. After OCR extraction, compare words with a dictionary of common words and correct missing umlauts accordingly.

7. Check Recent Issues and Discussions

The discussed Czech language issue (Discussion) indicates similar diacritic-related problems. You may want to check if other users have identified solutions for non-English character recognition.

If none of these steps resolve the issue, a custom training approach may be necessary.

Would you be able to share some sample OCR outputs along with images to further debug the issue?

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[sayinmehmet47]

This AI generated answer did not solve my problem

[GreatV]

You may need to fine-tune your model. please refer to https://paddlepaddle.github.io/PaddleOCR/latest/en/ppocr/model_train/finetune.html

from paddleocr import PaddleOCR
from PIL import Image, ImageDraw, ImageFont

ocr = PaddleOCR(use_angle_cls=True, lang="de", det_db_unclip_ratio=1.5)

img_path = "./Snipaste_2025-03-05_08-48-05.png"
# slice = {'horizontal_stride': 300, 'vertical_stride': 500, 'merge_x_thres': 50, 'merge_y_thres': 35}
# results = ocr.ocr(img_path, cls=True, slice=slice)
results = ocr.ocr(img_path, cls=True)

image = Image.open(img_path).convert("RGB")
draw = ImageDraw.Draw(image)
font = ImageFont.truetype("./doc/fonts/german.ttf", size=10)


for res in results:
    for line in res:
        box = [tuple(point) for point in line[0]]

        box = [(min(point[0] for point in box), min(point[1] for point in box)),
               (max(point[0] for point in box), max(point[1] for point in box))]
        txt = line[1][0]
        draw.rectangle(box, outline="red", width=2)
        draw.text((box[0][0], box[0][1] - 15), txt, fill="blue", font=font) 


image.save("result.jpg")