I want to cut out only the face from a person image with Python and save it ~ Face detection and trimming with face_recognition ~

things to do

this

like this

environment

MacOS Catalina 10.15.4
Python 3.7.6

What is face_recognition?

A library that can perform some image processing such as face detection using a trained model. It is said that dlib is used. https://github.com/ageitgey/

Repository

This is a code that uses face_recognition. https://github.com/komiyakomiyakomiya/face_trim

terminal

$ git https://github.com/komiyakomiyakomiya/face_trim.git

Library

opencv-python==4.2.0.34
face-recognition==1.3.0

Installation

terminal

$ pip install opencv-python==4.2.0.34 face-recognition==1.3.0

code

face_trim.py

import os
from pathlib import Path
import subprocess
import sys

import cv2
import face_recognition
from IPython.display import display
from IPython.display import Image


cwd = Path().resolve()


def exec_cmd(cmd):
    """Command execution"""
    #Delete any spaces before or after the cmd string->Divide by space and make a list
    cmd_split = cmd.strip().split()
    #Get standard output with stdout settings
    cp = subprocess.run(cmd_split, stdout=subprocess.PIPE)
    # cp = subprocess.check_output(cmd_split)
    if cp.returncode != 0:
        print(f'{cmd_split[0]} faild.', file=sys.stderr)
        sys.exit(1)
    #Returns if there is standard output
    if cp.stdout is not None:
        # bytes ->Decode to str
        return cp.stdout.decode('utf-8')


def get_face_location(img_path):
    """Get face coordinates"""
    img = face_recognition.load_image_file(img_path)
    # location = face_recognition.face_locations(img, model='cnn')
    location = face_recognition.face_locations(img, model='hog')
    print(location)
    # [(82, 175, 180, 76)]
    top = location[0][0]
    right = location[0][1]
    bottom = location[0][2]
    left = location[0][3]
    return top, right, bottom, left


def get_face_location_cli(img_path):
    """CLI tool face_Execute detection to get face coordinates
    load_image_file()Use this if the method cannot be used due to a bug"""
    #Detects face and Top, Right, Bottom,Command to output the coordinates of Left as standard
    cmd_face_detection = f'face_detection {img_path}'
    # cmd_face_detection = f'face_detection --model cnn {img_path}'
    #Receive standard output
    stdout = exec_cmd(cmd_face_detection)
    print(stdout)
    # /Users/USER_NAME/path/to/dir/input/Zinedine_Zidane_0001.jpg,89,181,192,77
    #List separated by commas
    stdout_list = stdout.strip().split(',')
    top = int(stdout_list[1])
    right = int(stdout_list[2])
    bottom = int(stdout_list[3])
    left = int(stdout_list[4])
    return top, right, bottom, left


def display_image(img_path):
    """Display image"""
    #Loading images
    img = cv2.imread(img_path)
    #Get extension
    format = os.path.splitext(img_path)[1]
    #Extension passed(format)Encoded in the format of
    decoded_bytes = cv2.imencode(format, img)[1].tobytes()
    print(cv2.imencode(format, img)[1])
    # [[255]
    # [216]
    # [255]
    # ...
    # [103]
    # [255]
    # [217]]
    # print(decoded_bytes)
    # b'\xff\xd8\xff\xe0\x00\x10JFIF\x00\x01\x01\x0......
    display(Image(data=decoded_bytes))


if __name__ == '__main__':
    #Please replace it with your favorite image
    file_name = f'Zinedine_Zidane_0001.jpg'
    #Where to put the original image
    input_path = f'{cwd}/../input'
    #Output destination of cropped image
    output_path = f'{cwd}/../output'
    #Create if there is no output directory
    os.makedirs(output_path, exist_ok=True)

    #Get face coordinates
    top, right, bottom, left = get_face_location(f'{input_path}/{file_name}')

    #Reading the original file
    img = cv2.imread(f'{input_path}/{file_name}')
    #display
    display_image(f'{input_path}/{file_name}')
    #trimming
    img_face = img[top:bottom, left:right]
    #Save to output directory
    cv2.imwrite(f'{output_path}/{file_name}', img_face)
    #display
    display_image(f'{output_path}/{file_name}')

Crop images in the directory together

if __name__ == '__main__':
    #Where to put the original image
    input_path = f'{cwd}/../input'
    #Output destination of cropped image
    output_path = f'{cwd}/../output'
    #Create if there is no output directory
    os.makedirs(output_path, exist_ok=True)

    #Generate path object
    path_obj = Path(input_path)
    #Pattern matching with glob
    files_path = path_obj.glob('*')
    #posix conversion
    files_path_posix = [file_path.as_posix() for file_path in files_path]
    print(files_path_posix)

    for file_path in files_path_posix:
        #Get file name
        file_name = file_path.split('/')[-1]
        #Get face coordinates
        top, right, bottom, left = get_face_location(file_path)
        #Reading the original file
        img = cv2.imread(file_path)
        #display
        display_image(file_path)
        #trimming
        img_face = img[top:bottom, left:right]
        #Save to output directory
        cv2.imwrite(f'{output_path}/{file_name}', img_face)
        #display
        display_image(f'{output_path}/{file_name}')

error

I sometimes got an error like this.

AttributeError: module 'face_recognition' has no attribute 'load_image_file'

The issue was also standing, but I couldn't solve it even if I tried what was written here. https://github.com/ageitgey/face_recognition/issues/318

When I gave up and tried the brute force method of getting the face coordinates from the standard output of the CLI tool, it was fixed before I knew it.

Cluster cropped images

I wrote an article here. If you do not mind

-Clustering image data of multiple people without correct label with FaceNet and outputting to different directories

The end

Thank you for reading until the end! Zidane has no meaning. I happened to be by my side.