Metadata-Version: 2.1
Name: ourcustompkg
Version: 0.2.1
Summary: A robust YOLOv7-based package designed for efficient toy car detection and comprehensive dataset management.
Home-page: https://github.com/NeuroLeapTeam/gesture_recognition.git
Author: Brandon & Moshiur
Author-email: brandon@neuroleapmail.com, moshiur@neuroleapmail.com
Project-URL: Bug Tracker, https://github.com/NeuroLeapTeam/gesture_recognition/issues
Project-URL: Documentation, https://github.com/NeuroLeapTeam/gesture_recognition/wiki
Project-URL: Source Code, https://github.com/NeuroLeapTeam/gesture_recognition
Keywords: YOLOv7,toy car detection,dataset management,computer vision,deep learning
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: torch>=1.7.0
Requires-Dist: torchvision>=0.8.0
Requires-Dist: opencv-python>=4.1.2
Requires-Dist: numpy>=1.18.5
Requires-Dist: Pillow>=7.2.0
Requires-Dist: tqdm>=4.41.0
Requires-Dist: mediapipe>=0.8.9
Requires-Dist: tensorflow>=2.4.0
Requires-Dist: matplotlib>=3.2.2
Requires-Dist: scipy>=1.4.1
Requires-Dist: pyyaml>=5.3.1
Requires-Dist: seaborn>=0.11.0
Requires-Dist: pandas>=1.1.5
Requires-Dist: scikit-learn>=0.24.1
Requires-Dist: requests>=2.23.0


OurCustomPkg: YOLOv7-based Toy Car Detection
============================================

Welcome to **OurCustomPkg**, a cutting-edge Python package designed for the detection of toy cars using the powerful YOLOv7 model. Additionally, the package integrates hand-tracking capabilities via MediaPipe, allowing for interactive and dynamic detection experiences.

Features
--------

*   **YOLOv7 Integration:** Utilize the state-of-the-art YOLOv7 model for accurate and efficient toy car detection.
*   **Multi-Source Input:** Supports images, video files, and real-time webcam feeds as input sources.
*   **Hand Tracking:** Employ MediaPipe's hand tracking to interact with detected objects in real-time.
*   **Highly Customizable:** Easily adjust detection parameters and extend functionalities according to your project needs.

Installation
------------

To get started with **OurCustomPkg**, you can install it directly from PyPI:

    pip install ourcustompkg

This command will install the package along with all the necessary dependencies, including PyTorch, OpenCV, and MediaPipe.

Getting Started
---------------

### Basic Usage

The primary script for toy car detection is `detect_car.py`, located in the `ourcustompkg/yolov7/` directory. Here's how to use it:

    python -m ourcustompkg.yolov7.detect_car --source <input_source> --weights <path_to_weights>

#### Example Commands

**Detect cars in an image:**

    python -m ourcustompkg.yolov7.detect_car --source data/images/car.jpg --weights yolov7.pt

**Detect cars from a video file:**

    python -m ourcustompkg.yolov7.detect_car --source data/videos/car_video.mp4 --weights yolov7.pt

**Real-time detection using a webcam:**

    python -m ourcustompkg.yolov7.detect_car --source 0 --weights yolov7.pt

### Hand Tracking Interaction

One of the standout features of **OurCustomPkg** is its integration of hand-tracking functionality using MediaPipe. When running the `detect_car.py` script, you can interact with detected cars using hand gestures tracked by your webcam.

### Command-Line Arguments

*   `--source`: Specifies the input source, which can be an image file, video file, or webcam feed.
*   `--weights`: Path to the YOLOv7 weights file. You can download pretrained weights from the official YOLOv7 repository.
*   `--img-size`: Sets the size of the input image for detection (default: 640).
*   `--conf-thres`: Confidence threshold for filtering weak detections (default: 0.25).
*   `--iou-thres`: IoU threshold for non-maximum suppression (default: 0.45).
*   `--device`: Specifies the device to run the model on (`cpu` or `cuda`).

### Advanced Usage

For advanced users, the `detect_car.py` script offers additional options to customize your detection pipeline:

*   Save detection results to a specific directory.
*   Toggle between different models or weight files.
*   Modify input processing techniques or adjust the output format.

Documentation
-------------

For more detailed information, including how to extend the package or contribute to its development, please visit our [official documentation](https://pypi.org/project/ourcustompkg/).

Contributing
------------

We welcome contributions to **OurCustomPkg**! If you have ideas for new features, enhancements, or bug fixes, please open an issue or submit a pull request on our [GitHub repository](https://github.com/NeuroLeapTeam/gesture_recognition).

License
-------

This project is licensed under the MIT License. You can view the full license [here](https://github.com/NeuroLeapTeam/gesture_recognition/blob/main/LICENSE).

Acknowledgments
---------------

*   **YOLOv7**: Our package is built upon the innovative YOLOv7 model, which has significantly advanced the field of real-time object detection.
*   **MediaPipe**: MediaPipe's hand tracking technology has enabled us to create a more interactive and user-friendly detection experience.

Contact
-------

For any questions, feedback, or support, feel free to reach out to the authors:

*   Brandon: [brandon@neuroleapmail.com](mailto:brandon@neuroleapmail.com)
*   Moshiur: [moshiur@neuroleapmail.com](mailto:moshiur@neuroleapmail.com)

* * *

Thank you for using **OurCustomPkg**! We hope it serves your toy car detection needs and inspires further innovation in your projects.
