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Deep Utils

Project description

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Deep Utils

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

Table of contents

Quick start

  1. Install:

    # 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 
    
  2. In python, import deep_utils and instantiate models:

    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')
    
  3. Detect an image:

    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

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0.4.2

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