mesen with dlib

0.py

import sys
import os
import dlib
import glob
import cv2
import numpy as np
import argparse
import base64
import time

def image_to_bytes(image):
    flag, buf = cv2.imencode('.png', image)
    return buf.tobytes()


def point_to_vector(p):
    return np.array([p.x, p.y])


def draw_black_line(image, positions):
    PADDING_VERTICAL_RATIO = 0.25
    PADDING_HORIZONTAL_RATIO = 0.4

    left = point_to_vector(positions['LEFT_EYE'])
    right = point_to_vector(positions['RIGHT_EYE'])

    left_top = np.array(left)
    left_bottom = np.array(left)

    right_top = np.array(right)
    right_bottom = np.array(right)

    horizontal_direction = right - left
    normal = np.array([horizontal_direction[1], -horizontal_direction[0]], int)
    normal = normal / np.linalg.norm(normal)

    # vertical
    left_height = np.linalg.norm(point_to_vector(positions['LEFT_EYE_BOTTOM_BOUNDARY']) - point_to_vector(positions['LEFT_EYE_TOP_BOUNDARY']))
    right_height = np.linalg.norm(point_to_vector(positions['RIGHT_EYE_BOTTOM_BOUNDARY']) - point_to_vector(positions['RIGHT_EYE_TOP_BOUNDARY']))

    height = max(left_height, right_height)
    left_top += np.array(height * PADDING_VERTICAL_RATIO * normal, int)
    left_bottom -= np.array(height * PADDING_VERTICAL_RATIO * normal, int)

    right_top += np.array(height * PADDING_VERTICAL_RATIO * normal, int)
    right_bottom -= np.array(height * PADDING_VERTICAL_RATIO * normal, int)

    horizontal_pad = np.array(PADDING_HORIZONTAL_RATIO * (right - left), int)
    left_top -= horizontal_pad
    left_bottom -= horizontal_pad
    right_top += horizontal_pad
    right_bottom += horizontal_pad

    cv2.fillPoly(image, [np.array([
        left_top,
        left_bottom,
        right_bottom,
        right_top,
    ])], color=(0, 0, 0), lineType=cv2.LINE_AA)


predictor_path = 'shape_predictor_68_face_landmarks.dat'
f = sys.argv[1]

def detect_face_landmarks(img, region):
    predictor = dlib.shape_predictor(predictor_path)
    shape = predictor(img, region)

    return {
        'LEFT_EYE': shape.part(37),
        'RIGHT_EYE': shape.part(46),
        'LEFT_EYE_BOTTOM_BOUNDARY': shape.part(42),
        'LEFT_EYE_TOP_BOUNDARY': shape.part(38),
        'RIGHT_EYE_BOTTOM_BOUNDARY': shape.part(47),
        'RIGHT_EYE_TOP_BOUNDARY': shape.part(45),
    }


img = cv2.imread(f)

detector = dlib.get_frontal_face_detector()
regions = detector(img, 1)
for i, region in enumerate(regions):
    # predictor = dlib.shape_predictor(predictor_path)
    # shape = predictor(img, region)
    # for part in shape.parts():
    #     cv2.circle(img, (part.x, part.y), 1, (0, 255, 0), thickness=-1, lineType=cv2.LINE_AA)

    position = detect_face_landmarks(img, region)
    draw_black_line(img, position)

sys.stdout.buffer.write(image_to_bytes(img))