OCR-License-Plate-Container-ID Computer Vision Project

OCR for License Plates and Container IDs Detection

Use this model to detect and recognize alphanumeric characters on objects like vehicle license plates and shipping container IDs. It’s an excellent way to get started with optical character recognition (OCR) tasks or a strong baseline for more specialized applications such as transportation monitoring and logistics automation.

For this model, we trained on a diverse dataset of 24,000 images, capturing a wide variety of real-world conditions and scenarios. These images include challenging environments like low-light settings, angled views, and varying distances from the object. While the complete model was trained on 24k images, we’ve made a sample of 50 curated images publicly available for users to explore and test.

These images are sourced from a combination of custom datasets and publicly available datasets on Roboflow Universe, ensuring broad generalization to real-world use cases. We've also applied augmentations to better capture the diversity of OCR tasks in the field:

• Preprocessing: Resize to 416x416 to maintain context and clarity across image sizes.

• Class Adjustments: Mapped character classes to fit standardized formats.

• Augmentations: Applied zoom (20% maximum), cropping, and other techniques to increase robustness in detecting numbers and characters in variable conditions.

We recommend using this model as a training checkpoint on your own data for more tailored results in your specific OCR application. By fine-tuning it with your unique dataset, you can improve its performance for specialized tasks.

This model excels at recognizing characters in common industrial and vehicular applications, making it a powerful tool for automation in various industries.