Metadata-Version: 2.1
Name: deep-utils
Version: 0.8.2
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/0.8.2.tar.gz
Description: [![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/pooya-mohammadi/deep_utils.git
           
            # or clone the repo
            git clone https://github.com/pooya-mohammadi/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)
        
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
