Hello everyone! Today I recommend to you a new open source dataset created by me: China-Balanced-License-Plate-Recognition-Dataset-330k. This is a high-quality, balanced Chinese license plate recognition dataset, which contains 330,000 pictures of various Chinese license plates. The dataset has been carefully designed to ensure excellent image quality and a balanced distribution of most types of license plates. This dataset is very suitable for training and evaluating license plate recognition models.
Compared with other datasets, the balanced distribution of China-Balanced-License-Plate-Recognition-Dataset-330k is that it covers most of the various types of Chinese license plates, avoiding accurate recognition caused by dataset skew when training the model rate decreased. This is very important for dealing with license plate recognition tasks in real-world scenarios.
In order to verify the practicability of the dataset, we used the first three layers of ResNet18 as the model infrastructure and CTC loss as the loss function for training. After testing, the model trained directly using this data set can well cope with the license plate recognition task of general parking lots.
At the same time, we will open more datasets in the future. The training code is already being sorted out and ready to be open sourced, including models and deployment codes will also be open sourced one after another. In order to support our continuous improvement and provide more high-quality open source resources, you are welcome to visit our GitHub repository for more details. If you find it helpful, please don't be mean to your Star!
The characteristics of the China-Balanced-License-Plate-Recognition-Dataset-330k dataset are as follows:
- High-quality images: Generated through careful design, the image quality is excellent.
- Balanced distribution: Contains various types of Chinese license plates to avoid data set skew affecting recognition accuracy.
- Large-scale: Contains 330,000 license plate pictures, which is very suitable for large-scale model training.
- Open source and free: This dataset is completely open source and free, and researchers and developers are welcome to use it.
We hope this data set can help everyone in their research and development work. At the same time, we also welcome your valuable comments and suggestions for our project. Let us work together to bring more valuable contributions to the field of license plate recognition.
In practical applications, license plate recognition technology has become an important part of intelligent transportation, intelligent security and other fields. By continuously optimizing datasets and models, we hope to provide better resources for researchers and developers to jointly promote the development of license plate recognition technology.
Thank you again for your attention and support to us. If you think our project is helpful to you, welcome to visit our GitHub repository for more details, and please don't forget to give our project a star to show your encouragement. Your support is our motivation to continue to improve and share more high-quality open source resources!
I wish you a happy use and look forward to making more breakthroughs in the field of license plate recognition with you!
Finally, thank you again for your support! If our project is helpful to you, please don't forget to point star! Thank you everyone!