https://github.com/nuhmanpk/yolo-helpers-docs
Some Helper functions for yolo-training
https://github.com/nuhmanpk/yolo-helpers-docs
Last synced: about 1 month ago
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Some Helper functions for yolo-training
- Host: GitHub
- URL: https://github.com/nuhmanpk/yolo-helpers-docs
- Owner: nuhmanpk
- License: mit
- Created: 2023-03-15T14:34:40.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-18T08:21:07.000Z (over 2 years ago)
- Last Synced: 2025-03-04T22:22:52.099Z (7 months ago)
- Language: Jupyter Notebook
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Yolo-helpers
This repository contains a Jupyter Notebook `helpers.ipynb` that includes various helper functions for training object detection models using YOLO (You Only Look Once) architecture.
YOLO is a state-of-the-art object detection system that is widely used in computer vision applications. This notebook provides a collection of helper functions that will be useful for computer vision engineers who are working with YOLO.
## Features
This notebook includes the following helper functions:
- split_data: This function can be used to split the data to train and test folder and genrate a txt files for both train and test files , which can be used in yaml file for training purposes.
- image_preprocessing: This function is used to preprocess images for YOLO training. It includes resizing the images, converting them to the appropriate format, and normalizing the pixel values.
- annotation_parser: This function is used to parse annotation files and extract the bounding box information for each object in the image.
- generate_anchors: This function is used to generate anchor boxes for YOLO.
- evaluate: This function is used to evaluate the performance of the YOLO model on a given dataset.
- draw_boxes: This function is used to draw the predicted bounding boxes on an image.
- crop_image: This function helps to crop the image at the roi provided.
- create_class_names_file: This function helps to create the class_names.txt files for training purposes.
## Contributing
If you have any suggestions for additional helper functions that could be included in this notebook, please feel free to contribute. You can submit a pull request with your changes, and I will review them as soon as possible.
## Compatibility
These helper functions are compatible with all versions of YOLO.
# Installation
To use these helper functions, simply download the helpers.ipynb file and run it in a Jupyter Notebook environment. No additional installation is required.
# License
This repository is licensed under the MIT License. Please see the LICENSE file for more information.
* Remember, with great YOLO power comes great object detection responsibility!