Python使用dlib(face_recognition)调整裁剪后的人脸图像的边距

问题描述 投票:1回答:1

我想调整裁切后的面部图像的边距。我当前的代码可以检测并修剪脸部。但是,裁剪的图像太紧,如下面的输出图像所示。

输入图像:

enter image description here

从我的代码输出图像:

enter image description here

所需的输出(增加余量并使其平方):

enter image description here

下面是我的代码:

import face_recognition
import cv2

img = face_recognition.load_image_file("test.png")
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

face_locations = face_recognition.face_locations(img_rgb)

for top, right, bottom, left in face_locations:
    # Draw a box around the face
    cv2.rectangle(img, (left, top), (right, bottom), (0, 0, 255), 2)

    crop_img = img_rgb[top:bottom, left:right]
    cv2.imwrite('test_crop.png', crop_img)
python opencv crop face-recognition dlib
1个回答
0
投票

代码:

使用scale_factor控制新的矩形大小。 M也可以使用其他公式。可能不需要使用abs

import face_recognition
import cv2


img = face_recognition.load_image_file("test.png")
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img_rgb_copy = img_rgb.copy()


## Define scale factor and window size
scale_factor = 1.1
sz1 = img_rgb.shape[1] * 2
sz2 = img_rgb.shape[0] * 2


face_locations = face_recognition.face_locations(img_rgb)

for top, right, bottom, left in face_locations:
    # Draw a box around the face
    #cv2.rectangle(img, (left, top), (right, bottom), (0, 0, 255), 2)

    crop_img = img_rgb[top:bottom, left:right]
    #cv2.imwrite('test_crop.png', crop_img)



    ## Calculate center points and rectangle side length
    width = right - left
    height = bottom - top
    cX = left + width // 2
    cY = top + height // 2
    M = (abs(width) + abs(height)) / 2


    ## Get the resized rectangle points
    newLeft = max(0, int(cX - scale_factor * M))
    newTop = max(0, int(cY - scale_factor * M))
    newRight = min(img_rgb.shape[1], int(cX + scale_factor * M))
    newBottom = min(img_rgb.shape[0], int(cY + scale_factor * M))


    ## Draw the circle and bounding boxes
    cv2.circle(img_rgb_copy, (cX, cY), radius=0, color=(0, 0, 255), thickness=2)
    cv2.rectangle(img_rgb_copy, (left, top), (right, bottom), (0, 0, 255), 2)
    cv2.rectangle(img_rgb_copy, (newLeft, newTop), (newRight, newBottom), (255, 0, 0), 2)


    ## Show the original image in window resized to double
    cv2.namedWindow('image', cv2.WINDOW_NORMAL)
    cv2.resizeWindow('image', sz1, sz2)
    cv2.imshow("image", img_rgb_copy)
    cv2.waitKey(0)


cv2.destroyAllWindows()

图像:

enter image description here

方法:

获得给定区域的中心点(cX, cY),并通过从两个(cX - M,cY - M)中减去相同的值,从中获得图像的新左上角。因此,右上角将为(cX + M, cY + M)。您可以使用比例因子,例如M * p而不是M,其中p将控制新区域的大小。

中心点:

width = right - left
height = bottom - top

centerX = left + (width / 2)
centerY = top + (height / 2)

M = (abs(width) + abs(height)) / 2

0 <= p < 1, for smaller crop than given in a side
p > 1, for larger crop margin

此外,新作物的图像可能超出范围。为了解决这个问题,可以完成newTop = max(0, newTop)newRight = min(imageWidth, newRight)等。您可以在此处找到一个演示,

https://www.desmos.com/calculator/bgn9dobkjt

enter image description here

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