License plate recognition

[Spycka]

Hello. Would you ba able to share the License plate recognition model with me. I would like to try it in my project.

[GreatV]

Hello! I cannot directly share a license plate recognition model file, but I can give you guidance on how to obtain or train one, based on the provided documents and related discussions.

From the discussion referenced (link), it is clear that frameworks like PaddleOCR support training and customization of detection models for tasks such as license plate recognition—even for tilted or skewed plates.

Here are the key points to help you move forward:

How to Obtain a License Plate Recognition Model

1. Use Existing OCR Frameworks:

   • PaddleOCR, an open-source project, provides both detection and recognition models that can be used for license plate recognition.
   • Check PaddleOCR's official model list and documentation for pretrained models:
     • https://github.com/PaddlePaddle/PaddleOCR

2. Custom Training for Skewed/Rotated Plates:

   • According to the discussion, you can retrain the detection model to better fit skewed or tilted license plates by adjusting the annotation (label) style to better fit the plate's exact shape.
   • PaddleOCR supports training with customized datasets. You would need to annotate your license plate data with quadrilateral bounding boxes closely fitting the plate, then train the detection model (e.g., en_PP-OCRv3_det) following the PaddleOCR training documentation.

3. Pipeline:

   • Typical pipeline involves a detection model (to find and crop out the plate) followed by a recognition model (to read the numbers and letters).
   • Pretrained detection and recognition models for general text often work decently for license plates but may be improved with fine-tuning on license plate-specific data.

Resources

• PaddleOCR Tutorials:
  Official quick start guide
• Custom Data Training:
  Detection model training details
• Model Zoo & Pretrained Models:
  PaddleOCR Model List

Direct Model Sharing

• If you need a ready-to-use model, you can download PaddleOCR's detection and recognition models as described above.
• For license plate-specific models, you may need to search for open datasets (e.g., OpenALPR, CCPD) and train a model, as openly shared, well-tuned license plate models may not always be available for direct download due to privacy or restriction reasons.

If you describe your use case or preferred framework/language further, I can suggest more targeted resources or code snippets!

Related Discussion:

• Is it possible to train a detection model that can detect the skewed/tilt word/license plate? (explains custom label shape and retraining options)

Let me know if you need help with specific code or setup steps!

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