# Model Trainer
Model Trainer is a Python package designed to simplify the process of training YOLO (You Only Look Once) models for object detection tasks. With Model Trainer, users can easily train YOLO models using custom datasets and split their data into training, validation, and testing sets. The package provides classes for both model training and data splitting, allowing users to efficiently manage their training pipeline. Additionally, Model Trainer includes functionality for saving the best-performing model weights, making it easy to deploy trained models for inference tasks.
## Features
- Train YOLO models with custom datasets
- Split datasets into training, validation, and testing sets
- Save best-performing model weights for deployment
## Installation
You can install Model Trainer using pip:
```bash
pip install Dataset_Trainer
```
## Usage
### Training a YOLO Model
```python
from Dataset_Trainer import YOLO_Trainer
# Initialize YOLO Trainer with data.yaml folder path and destination folder for best weights
trainer = YOLO_Trainer(Data_yaml_fold_path='path/to/data.yaml', Best_Weight_dest='path/to/destination', epochs=50)
# Select YOLO model version and configuration
trainer.model_selection()
# Train the selected model
trainer.model_training()
# Save the best-performing model weights
trainer.model_saving()
```
### Splitting Data
```python
from Dataset_Trainer import Data_Splitter
# Initialize Data Splitter with data folder, destination folder, and number of classes
splitter = Data_Splitter(data_folder='path/to/data', dest_fold='path/to/destination', no_classes=3)
# Collect paths and names of classes
splitter.class_path_folder()
# Split the data into train, validation, and test sets
splitter.split()
```
## License
Model Trainer is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Support
For support, please open an issue on our [GitHub repository](https://github.com/yourusername/Model_Trainer/issues).
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"description": "\r\n# Model Trainer\r\n\r\n\r\n\r\nModel Trainer is a Python package designed to simplify the process of training YOLO (You Only Look Once) models for object detection tasks. With Model Trainer, users can easily train YOLO models using custom datasets and split their data into training, validation, and testing sets. The package provides classes for both model training and data splitting, allowing users to efficiently manage their training pipeline. Additionally, Model Trainer includes functionality for saving the best-performing model weights, making it easy to deploy trained models for inference tasks.\r\n\r\n\r\n\r\n## Features\r\n\r\n\r\n\r\n- Train YOLO models with custom datasets\r\n\r\n- Split datasets into training, validation, and testing sets\r\n\r\n- Save best-performing model weights for deployment\r\n\r\n\r\n\r\n## Installation\r\n\r\n\r\n\r\nYou can install Model Trainer using pip:\r\n\r\n\r\n\r\n```bash\r\n\r\npip install Dataset_Trainer\r\n\r\n```\r\n\r\n\r\n\r\n## Usage\r\n\r\n\r\n\r\n### Training a YOLO Model\r\n\r\n\r\n\r\n```python\r\n\r\nfrom Dataset_Trainer import YOLO_Trainer\r\n\r\n\r\n\r\n# Initialize YOLO Trainer with data.yaml folder path and destination folder for best weights\r\n\r\ntrainer = YOLO_Trainer(Data_yaml_fold_path='path/to/data.yaml', Best_Weight_dest='path/to/destination', epochs=50)\r\n\r\n\r\n\r\n# Select YOLO model version and configuration\r\n\r\ntrainer.model_selection()\r\n\r\n\r\n\r\n# Train the selected model\r\n\r\ntrainer.model_training()\r\n\r\n\r\n\r\n# Save the best-performing model weights\r\n\r\ntrainer.model_saving()\r\n\r\n```\r\n\r\n\r\n\r\n### Splitting Data\r\n\r\n\r\n\r\n```python\r\n\r\nfrom Dataset_Trainer import Data_Splitter\r\n\r\n\r\n\r\n# Initialize Data Splitter with data folder, destination folder, and number of classes\r\n\r\nsplitter = Data_Splitter(data_folder='path/to/data', dest_fold='path/to/destination', no_classes=3)\r\n\r\n\r\n\r\n# Collect paths and names of classes\r\n\r\nsplitter.class_path_folder()\r\n\r\n\r\n\r\n# Split the data into train, validation, and test sets\r\n\r\nsplitter.split()\r\n\r\n```\r\n\r\n\r\n\r\n## License\r\n\r\n\r\n\r\nModel Trainer is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n## Support\r\n\r\n\r\n\r\nFor support, please open an issue on our [GitHub repository](https://github.com/yourusername/Model_Trainer/issues).\r\n",
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