Code Usage Guide

1. Download the Dataset: Once you have downloaded the dataset, modify the train.py script by setting the --train-data-path and --val-data-path to the absolute path of the extracted dataset folder.
2. Download Pre-trained Weights: Obtain the pre-trained weights required for training.
3. Set Pre-trained Weights Path: In the train.py script, set the --weights parameter to the path where you have saved the pre-trained weights.
4. Start Training: With the dataset path --data-path and the pre-trained weights path --weights correctly set, you can now start training using the train.py script. During the training process, a class_indices.json file will be automatically generated.
5. Use Your Own Dataset: If you are using your own dataset, please arrange it according to the classification structure (i.e., one category corresponds to one folder, and within this, another folder for each package). Also, set the num_classes in both the training and prediction scripts to match the number of categories in your dataset.