質問編集履歴
1
修正依頼
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -67,3 +67,241 @@
|
|
|
67
67
|
|
|
68
68
|
|
|
69
69
|
理由がわかる方、教えていただけたら幸いです。宜しくお願い致します。
|
|
70
|
+
|
|
71
|
+
|
|
72
|
+
|
|
73
|
+
|
|
74
|
+
|
|
75
|
+
|
|
76
|
+
|
|
77
|
+
### 追加事項
|
|
78
|
+
|
|
79
|
+
programの全体を載せます。宜しくお願い致します。
|
|
80
|
+
|
|
81
|
+
|
|
82
|
+
|
|
83
|
+
```python
|
|
84
|
+
|
|
85
|
+
import cv2
|
|
86
|
+
|
|
87
|
+
import numpy as np
|
|
88
|
+
|
|
89
|
+
import math
|
|
90
|
+
|
|
91
|
+
import dlib
|
|
92
|
+
|
|
93
|
+
import os
|
|
94
|
+
|
|
95
|
+
import glob
|
|
96
|
+
|
|
97
|
+
import time
|
|
98
|
+
|
|
99
|
+
|
|
100
|
+
|
|
101
|
+
def fitting_rotated_image(img, angle):
|
|
102
|
+
|
|
103
|
+
# 画像の縦、横のサイズを取得する
|
|
104
|
+
|
|
105
|
+
height, width = img.shape[:2]
|
|
106
|
+
|
|
107
|
+
# 画像の中心値を取得
|
|
108
|
+
|
|
109
|
+
center = (int(width/2), int(height/2))
|
|
110
|
+
|
|
111
|
+
# 度からラジアンに変換(deg to rad)
|
|
112
|
+
|
|
113
|
+
radians = np.deg2rad(angle)
|
|
114
|
+
|
|
115
|
+
# 回転の変換行列
|
|
116
|
+
|
|
117
|
+
M = cv2.getRotationMatrix2D(center, angle, 1.0)
|
|
118
|
+
|
|
119
|
+
|
|
120
|
+
|
|
121
|
+
new_width = int(abs(np.sin(radians) * height) + abs(np.cos(radians) * width))
|
|
122
|
+
|
|
123
|
+
new_height = int(abs(np.sin(radians) * width) + abs(np.cos(radians) * height))
|
|
124
|
+
|
|
125
|
+
|
|
126
|
+
|
|
127
|
+
M[0,2] += int((new_width-width)/2)
|
|
128
|
+
|
|
129
|
+
M[1,2] += int((new_height-height)/2)
|
|
130
|
+
|
|
131
|
+
|
|
132
|
+
|
|
133
|
+
# アファイン変換した画像を返す
|
|
134
|
+
|
|
135
|
+
return cv2.warpAffine(img, M, (new_width, new_height))
|
|
136
|
+
|
|
137
|
+
|
|
138
|
+
|
|
139
|
+
start = time.time()
|
|
140
|
+
|
|
141
|
+
|
|
142
|
+
|
|
143
|
+
# 顔の位置を取得する
|
|
144
|
+
|
|
145
|
+
detector = dlib.get_frontal_face_detector()
|
|
146
|
+
|
|
147
|
+
# 顔の68箇所の位置の座標を取得する
|
|
148
|
+
|
|
149
|
+
predictor = dlib.shape_predictor('./shape_predictor_68_face_landmarks.dat')
|
|
150
|
+
|
|
151
|
+
|
|
152
|
+
|
|
153
|
+
# ディレクトリ内の画像を指定
|
|
154
|
+
|
|
155
|
+
image_list = glob.glob('./~/*')
|
|
156
|
+
|
|
157
|
+
count = 1
|
|
158
|
+
|
|
159
|
+
pro_time = 0
|
|
160
|
+
|
|
161
|
+
# 新しいディレクトリを作成
|
|
162
|
+
|
|
163
|
+
os.makedirs('~', exist_ok = True)
|
|
164
|
+
|
|
165
|
+
# for文で一枚ずつ処理していく
|
|
166
|
+
|
|
167
|
+
for image in image_list:
|
|
168
|
+
|
|
169
|
+
pro_start = time.time()
|
|
170
|
+
|
|
171
|
+
pro_time += 1
|
|
172
|
+
|
|
173
|
+
print("Processint Time :", pro_time)
|
|
174
|
+
|
|
175
|
+
# 処理する画像を指定
|
|
176
|
+
|
|
177
|
+
im = cv2.imread(image, cv2.IMREAD_COLOR)
|
|
178
|
+
|
|
179
|
+
|
|
180
|
+
|
|
181
|
+
# 画像が見つからない場合
|
|
182
|
+
|
|
183
|
+
if im is None:
|
|
184
|
+
|
|
185
|
+
print("count:", count, '画像が見つかりません')
|
|
186
|
+
|
|
187
|
+
#exit()
|
|
188
|
+
|
|
189
|
+
continue
|
|
190
|
+
|
|
191
|
+
|
|
192
|
+
|
|
193
|
+
rects = detector(im, 1)
|
|
194
|
+
|
|
195
|
+
|
|
196
|
+
|
|
197
|
+
if len(rects) == 0:
|
|
198
|
+
|
|
199
|
+
print("count:", count, '顔が抽出されませんでした')
|
|
200
|
+
|
|
201
|
+
#exit()
|
|
202
|
+
|
|
203
|
+
continue
|
|
204
|
+
|
|
205
|
+
|
|
206
|
+
|
|
207
|
+
for index, rect in enumerate(rects):
|
|
208
|
+
|
|
209
|
+
|
|
210
|
+
|
|
211
|
+
# 顔だけ切り出す
|
|
212
|
+
|
|
213
|
+
rectWidth = rect.width()
|
|
214
|
+
|
|
215
|
+
rectHeight = rect.height()
|
|
216
|
+
|
|
217
|
+
rectCenter = rect.center()
|
|
218
|
+
|
|
219
|
+
x_start = rectCenter.x - rectWidth
|
|
220
|
+
|
|
221
|
+
x_end = x_start + rectWidth * 2
|
|
222
|
+
|
|
223
|
+
y_start = rectCenter.y - rectHeight
|
|
224
|
+
|
|
225
|
+
y_end = y_start + rectHeight * 2
|
|
226
|
+
|
|
227
|
+
face_im = im[y_start:y_end, x_start:x_end]
|
|
228
|
+
|
|
229
|
+
|
|
230
|
+
|
|
231
|
+
# 顔の角度を修正
|
|
232
|
+
|
|
233
|
+
points = []
|
|
234
|
+
|
|
235
|
+
for point in predictor(im, rect).parts():
|
|
236
|
+
|
|
237
|
+
points.append([int(point.x), int(point.y)])
|
|
238
|
+
|
|
239
|
+
|
|
240
|
+
|
|
241
|
+
x_diff = points[45][0] - points[36][0]
|
|
242
|
+
|
|
243
|
+
y_diff = points[45][1] - points[36][1]
|
|
244
|
+
|
|
245
|
+
angle = math.degrees(math.atan2(y_diff, x_diff))
|
|
246
|
+
|
|
247
|
+
rotated_im = fitting_rotated_image(face_im, angle)
|
|
248
|
+
|
|
249
|
+
|
|
250
|
+
|
|
251
|
+
# 回転後の画像で顔検出して画像保存
|
|
252
|
+
|
|
253
|
+
rotated_rects = detector(rotated_im, 1)
|
|
254
|
+
|
|
255
|
+
if len(rotated_rects) == 0:
|
|
256
|
+
|
|
257
|
+
print("count:", count, '顔が抽出されませんでした')
|
|
258
|
+
|
|
259
|
+
continue
|
|
260
|
+
|
|
261
|
+
|
|
262
|
+
|
|
263
|
+
else:
|
|
264
|
+
|
|
265
|
+
rotated_rect = rotated_rects[0]
|
|
266
|
+
|
|
267
|
+
x_start = rotated_rect.left()
|
|
268
|
+
|
|
269
|
+
x_end = rotated_rect.right()
|
|
270
|
+
|
|
271
|
+
y_start = rotated_rect.top()
|
|
272
|
+
|
|
273
|
+
y_end = rotated_rect.bottom()
|
|
274
|
+
|
|
275
|
+
cropped_im = rotated_im[y_start:y_end, x_start:x_end]
|
|
276
|
+
|
|
277
|
+
|
|
278
|
+
|
|
279
|
+
cv2.imwrite('./~.jpg'.format(count), cropped_im)
|
|
280
|
+
|
|
281
|
+
pro_finish = time.time()
|
|
282
|
+
|
|
283
|
+
|
|
284
|
+
|
|
285
|
+
print("count", count, "finish.")
|
|
286
|
+
|
|
287
|
+
print("Processing Time:", pro_finish - pro_start, "sec")
|
|
288
|
+
|
|
289
|
+
|
|
290
|
+
|
|
291
|
+
count += 1
|
|
292
|
+
|
|
293
|
+
|
|
294
|
+
|
|
295
|
+
print("\n")
|
|
296
|
+
|
|
297
|
+
|
|
298
|
+
|
|
299
|
+
finish = time.time()
|
|
300
|
+
|
|
301
|
+
|
|
302
|
+
|
|
303
|
+
print("All Processing Time:", finish - start, "sec")
|
|
304
|
+
|
|
305
|
+
print(count, "face")
|
|
306
|
+
|
|
307
|
+
```
|