Use LPRNet for license plate recognition.
[Instructions]
1. 1_train.ipynb
Perform training.
Set the parameters:
• learning_rate: learning rate
• train_img_dirs: folder of training images
• test_img_dirs: test image folder
• train_batch_size: training batch size
• test_batch_size: test batch size
• save_interval: save interval
• max_epoch: the maximum number of training epochs
• save_folder: the folder path where the model is saved
• pretrained_model: the file path of the pretrained model
After the setting is completed, it can be executed.
2. 2_inference.ipynb
Perform inference.
Set the parameters:
• test_img: test image file path
• pretrained_model: the file path of the pretrained model
After the setting is completed, it can be executed.
After execution, the result of the inference can be obtained.
3. 3_inference_folder.ipynb
Perform inference on folder files.
Set the parameters:
• test_img_dirs: test image folder path
• pretrained_model: the file path of the pretrained model
After the setting is completed, it can be executed.
After execution, the result of the inference can be obtained.
This SDK is built in AppForAI - AI Dev Tools.
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