Spaces:
Configuration error
Configuration error
File size: 5,728 Bytes
e5ba844 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 | # coding: utf-8
import cv2
import numpy as np
class BBox(object):
# bbox is a list of [left, right, top, bottom]
def __init__(self, bbox):
self.left = bbox[0]
self.right = bbox[1]
self.top = bbox[2]
self.bottom = bbox[3]
self.x = bbox[0]
self.y = bbox[2]
self.w = bbox[1] - bbox[0]
self.h = bbox[3] - bbox[2]
# scale to [0,1]
def projectLandmark(self, landmark):
landmark_ = np.asarray(np.zeros(landmark.shape))
for i, point in enumerate(landmark):
landmark_[i] = ((point[0]-self.x)/self.w, (point[1]-self.y)/self.h)
return landmark_
# landmark of (5L, 2L) from [0,1] to real range
def reprojectLandmark(self, landmark):
landmark_ = np.asarray(np.zeros(landmark.shape))
for i, point in enumerate(landmark):
x = point[0] * self.w + self.x
y = point[1] * self.h + self.y
landmark_[i] = (x, y)
return landmark_
def drawLandmark(img, bbox, landmark):
'''
Input:
- img: gray or RGB
- bbox: type of BBox
- landmark: reproject landmark of (5L, 2L)
Output:
- img marked with landmark and bbox
'''
img_ = img.copy()
cv2.rectangle(img_, (bbox.left, bbox.top),
(bbox.right, bbox.bottom), (0, 0, 255), 2)
for x, y in landmark:
cv2.circle(img_, (int(x), int(y)), 3, (0, 255, 0), -1)
return img_
def drawLandmark_multiple(img, bbox, landmark):
'''
Input:
- img: gray or RGB
- bbox: type of BBox
- landmark: reproject landmark of (5L, 2L)
Output:
- img marked with landmark and bbox
'''
cv2.rectangle(img, (bbox.left, bbox.top),
(bbox.right, bbox.bottom), (0, 0, 255), 2)
for x, y in landmark:
cv2.circle(img, (int(x), int(y)), 2, (0, 255, 0), -1)
return img
def drawLandmark_Attribute(img, bbox, landmark, gender, age):
'''
Input:
- img: gray or RGB
- bbox: type of BBox
- landmark: reproject landmark of (5L, 2L)
Output:
- img marked with landmark and bbox
'''
cv2.rectangle(img, (bbox.left, bbox.top),
(bbox.right, bbox.bottom), (0, 0, 255), 2)
for x, y in landmark:
cv2.circle(img, (int(x), int(y)), 3, (0, 255, 0), -1)
if gender.argmax() == 0:
# -1->female, 1->male; -1->old, 1->young
cv2.putText(img, 'female', (int(bbox.left), int(bbox.top)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 3)
else:
cv2.putText(img, 'male', (int(bbox.left), int(bbox.top)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 3)
if age.argmax() == 0:
cv2.putText(img, 'old', (int(bbox.right), int(bbox.bottom)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 3)
else:
cv2.putText(img, 'young', (int(bbox.right), int(bbox.bottom)),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 3)
return img
def drawLandmark_only(img, landmark):
'''
Input:
- img: gray or RGB
- bbox: type of BBox
- landmark: reproject landmark of (5L, 2L)
Output:
- img marked with landmark and bbox
'''
img_ = img.copy()
# cv2.rectangle(img_, (bbox.left, bbox.top), (bbox.right, bbox.bottom), (0,0,255), 2)
for x, y in landmark:
cv2.circle(img_, (int(x), int(y)), 3, (0, 255, 0), -1)
return img_
def processImage(imgs):
'''
Subtract mean and normalize, imgs [N, 1, W, H]
'''
imgs = imgs.astype(np.float32)
for i, img in enumerate(imgs):
m = img.mean()
s = img.std()
imgs[i] = (img-m)/s
return imgs
def flip(face, landmark):
'''
flip a face and its landmark
'''
face_ = cv2.flip(face, 1) # 1 means flip horizontal
landmark_flip = np.asarray(np.zeros(landmark.shape))
for i, point in enumerate(landmark):
landmark_flip[i] = (1-point[0], point[1])
# for 5-point flip
landmark_flip[[0, 1]] = landmark_flip[[1, 0]]
landmark_flip[[3, 4]] = landmark_flip[[4, 3]]
# for 19-point flip
# landmark_flip[[0,9]] = landmark_flip[[9,0]]
# landmark_flip[[1,8]] = landmark_flip[[8,1]]
# landmark_flip[[2,7]] = landmark_flip[[7,2]]
# landmark_flip[[3,6]] = landmark_flip[[6,3]]
# landmark_flip[[4,11]] = landmark_flip[[11,4]]
# landmark_flip[[5,10]] = landmark_flip[[10,5]]
# landmark_flip[[12,14]] = landmark_flip[[14,12]]
# landmark_flip[[15,17]] = landmark_flip[[17,15]]
return (face_, landmark_flip)
def scale(landmark):
'''
scale the landmark from [0,1] to [-1,1]
'''
landmark_ = np.asarray(np.zeros(landmark.shape))
lanmark_ = (landmark-0.5)*2
return landmark_
def check_bbox(img, bbox):
'''
Check whether bbox is out of the range of the image
'''
img_w, img_h = img.shape
if bbox.x > 0 and bbox.y > 0 and bbox.right < img_w and bbox.bottom < img_h:
return True
else:
return False
def rotate(img, bbox, landmark, alpha):
"""
given a face with bbox and landmark, rotate with alpha
and return rotated face with bbox, landmark (absolute position)
"""
center = ((bbox.left+bbox.right)/2, (bbox.top+bbox.bottom)/2)
rot_mat = cv2.getRotationMatrix2D(center, alpha, 1)
img_rotated_by_alpha = cv2.warpAffine(img, rot_mat, img.shape)
landmark_ = np.asarray([(rot_mat[0][0]*x+rot_mat[0][1]*y+rot_mat[0][2],
rot_mat[1][0]*x+rot_mat[1][1]*y+rot_mat[1][2]) for (x, y) in landmark])
face = img_rotated_by_alpha[bbox.top:bbox.bottom+1, bbox.left:bbox.right+1]
return (face, landmark_)
|