Metadata-Version: 2.1
Name: deep-utils
Version: 0.4.2
Summary: Deep Utils
Home-page: UNKNOWN
Author: Pooya Mohammadi Kazaj
Author-email: pooyamohammadikazaj@gmial.com
License: UNKNOWN
Download-URL: https://github.com/Practical-AI/deep_utils/archive/refs/tags/0.4.2.tar.gz
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: requests
Requires-Dist: tqdm

[![Downloads](https://static.pepy.tech/badge/deep_utils)](https://pepy.tech/project/deep_utils) [![PyPI](https://img.shields.io/pypi/v/deep_utils.svg)](https://pypi.python.org/pypi/deep_utils)
# Deep Utils 

This repository contains the most frequently used deep learning modules and functions.


## Table of contents

* [Table of contents](#table-of-contents)
* [Quick start](#quick-start)
* [References](#references)

## Quick start

1. Install:

    ```bash
    # With pip:
    pip install deep_utils

    # or from the repo
    pip install git+https://github.com/Practical-AI/deep_utils.git

    # or clone the repo
    git clone https://github.com/Practical-AI/deep_utils.git deep_utils
    pip install -U deep_utils 
   ```

1. In python, import deep_utils and instantiate models:

    ```python
    from deep_utils import face_detector_loader, list_face_detection_models

   # list all the available models first 
   list_face_detection_models()

   # Create a face detection model using SSD
   face_detector = face_detector_loader('SSDCV2CaffeFaceDetector')


1. Detect an image:

    ```python
    import cv2
    from deep_utils import show_destroy_cv2, Box

    # Load an image
    img = cv2.imread(<image path>)

    # Detect the faces
    boxes, confidences = face_detector.detect_faces(img)

    # Draw detected boxes on the image 
    img = Box.put_box(img, boxes)

    # show the results
    show_destroy_cv2(img) 
    ```
## References

1. Tim Esler's facenet-pytorch repo: [https://github.com/timesler/facenet-pytorch](https://github.com/timesler/facenet-pytorch)


