-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathhistory_log_show.py
More file actions
348 lines (290 loc) · 15.2 KB
/
history_log_show.py
File metadata and controls
348 lines (290 loc) · 15.2 KB
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
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2 as cv
import numpy as np
import time
import argparse
def get_args(data_end_row):
# ターミナルから実行する際に、再生の仕方を設定できます
# --start <int> 再生を始める行を指定できます
# --end <int> 再生を終える行を指定できます
# --pause_time <bool> 1行ごと(1回分の16フレーム分シーケンス)にポーズする時間を入れるか(一瞬止めるか)
parser = argparse.ArgumentParser()
parser.add_argument("--start", type=int, default=0)
parser.add_argument("--end", type=int, default=data_end_row)
parser.add_argument("--pause_time", type=bool, default=False)
args = parser.parse_args()
return args
# TODO fps指定できるようにする
def main():
csv_path = 'model/point_history_classifier/point_history_allkeypoints.csv'
# DATA_RANGE = 672 + 1
csv_classifier_label_path = 'model/point_history_classifier/point_history_classifier_label_allkeypoints.csv'
with open(csv_path, 'r', newline="") as csvfile:
data = csvfile.readlines()
# ジェスチャのラベルデータを保持
with open(csv_classifier_label_path, 'r', newline='', encoding="utf_8") as csvlabelfile:
labeldata = csvlabelfile.readlines()
# 引数解析
args = get_args(len(data))
start_row = args.start
end_row = args.end
pause = args.pause_time
debug_image = np.zeros((540, 960, 3))
for i, row in enumerate(data):
if i < start_row or i > end_row:
continue
# row は 1行分の生データ(string型、, , ,..)
# ==============================================
### 実際に使うデータとして
### row_data, gesture_label, row_id の前処理をする
# ==============================================
# ","で長いStringを分割してlistに変換
row_data = row.split(',')
# 先頭のデータ(label番号)の要素を削除し、値(label番号)をintに変換して取得
gesture_label = int( row_data.pop(0) )
# listの中身をstring配列からfloat配列に変換
row_data = [float(s) for s in row_data] # row_dataは一次元
# このforループが処理しているデータ行番号を、row_idで保持
row_id = i + 1
# ==============================================
# ジェスチャ番号を対応するラベル番号の文字列に変換(gesture_label + 1 の行のジェスチャ名を取得)
gesture_label_str = labeldata[gesture_label]
# row_data を 16フレームに分割(1行に (キー押した時点にその時までの)16フレームが全部ある)
row_data_splited = np.array_split(row_data, 16)
# raw_data_splitedは2次元配列[array([, , , ])←1フレーム目全点2*21, array([,,,])←2フレーム目全点2*21,...]
# 各フレームごとにデータ描画
# 16回ループ seqは1次元の 2 * 21 要素の配列 各フレーム(seq)において、瞬間の全点の動きを計算
for seq in row_data_splited:
# 1次元配列の2*21要素のlistを2要素list * 21要素の2次元listにする
# [[x0,y0],[x1,y1],[x2,y2],[x3,y3],[x4,y4]...[x20,y20]]にする
seq = np.reshape(seq,[21,2]).tolist() # 外側から個数指定
'''ここでseqは21要素の各xyの2次元配列 print(seq)>>>
# ex)
# [[ 0. 0. ]
# [-0.065625 -0.01666667]
# [-0.1125 -0.06296296]
# [-0.14270833 -0.12777778]
# [-0.1625 -0.2 ]
# [-0.08333333 -0.21296296]
# [-0.1125 -0.32962963]
# [-0.12916667 -0.40925926]
# [-0.14583333 -0.48148148]
# [-0.05625 -0.39074074]
# [-0.06770833 -0.48888889]
# [-0.078125 -0.57777778]
# [ 0.00208333 -0.24444444]
# [-0.00208333 -0.39259259]
# [-0.00416667 -0.49259259]
# [-0.01041667 -0.57962963]
# [ 0.046875 -0.22222222]
# [ 0.06666667 -0.33703704]
# [ 0.08125 -0.41111111]
# [ 0.08854167 -0.48518519]]
'''
# データから位置計算処理
debug_image = draw_landmarks(debug_image, seq)
# 情報表示
debug_image = draw_info(debug_image, row_id, gesture_label_str)
# 画面描画
cv.imshow('CSV data reproduction', debug_image)
# debug_imageリセット
debug_image = np.zeros((540, 960, 3))
# キー処理(ESC:終了)
key = cv.waitKey(10)
if key == 27: # ESC
exit()
# 1秒間ポーズ
if pause: time.sleep(1)
cv.destroyAllWindows()
def draw_landmarks(image, landmark_point):
# 描画に適した値に加工
# (小さすぎる値の拡大、原点の違いを埋める平行移動,floatをintに変換)
landmark_point = list((int(x * 800 + 500), int(y * 800 + 500)) for x,y in landmark_point)
# 接続線
if len(landmark_point) > 0:
# 親指
cv.line(image, tuple(landmark_point[2]), tuple(landmark_point[3]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[2]), tuple(landmark_point[3]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[3]), tuple(landmark_point[4]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[3]), tuple(landmark_point[4]),
(255, 255, 255), 2)
# 人差指
cv.line(image, tuple(landmark_point[5]), tuple(landmark_point[6]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[5]), tuple(landmark_point[6]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[6]), tuple(landmark_point[7]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[6]), tuple(landmark_point[7]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[7]), tuple(landmark_point[8]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[7]), tuple(landmark_point[8]),
(255, 255, 255), 2)
# 中指
cv.line(image, tuple(landmark_point[9]), tuple(landmark_point[10]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[9]), tuple(landmark_point[10]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[10]), tuple(landmark_point[11]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[10]), tuple(landmark_point[11]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[11]), tuple(landmark_point[12]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[11]), tuple(landmark_point[12]),
(255, 255, 255), 2)
# 薬指
cv.line(image, tuple(landmark_point[13]), tuple(landmark_point[14]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[13]), tuple(landmark_point[14]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[14]), tuple(landmark_point[15]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[14]), tuple(landmark_point[15]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[15]), tuple(landmark_point[16]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[15]), tuple(landmark_point[16]),
(255, 255, 255), 2)
# 小指
cv.line(image, tuple(landmark_point[17]), tuple(landmark_point[18]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[17]), tuple(landmark_point[18]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[18]), tuple(landmark_point[19]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[18]), tuple(landmark_point[19]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[19]), tuple(landmark_point[20]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[19]), tuple(landmark_point[20]),
(255, 255, 255), 2)
# 手の平
cv.line(image, tuple(landmark_point[0]), tuple(landmark_point[1]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[0]), tuple(landmark_point[1]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[1]), tuple(landmark_point[2]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[1]), tuple(landmark_point[2]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[2]), tuple(landmark_point[5]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[2]), tuple(landmark_point[5]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[5]), tuple(landmark_point[9]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[5]), tuple(landmark_point[9]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[9]), tuple(landmark_point[13]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[9]), tuple(landmark_point[13]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[13]), tuple(landmark_point[17]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[13]), tuple(landmark_point[17]),
(255, 255, 255), 2)
cv.line(image, tuple(landmark_point[17]), tuple(landmark_point[0]),
(0, 0, 0), 6)
cv.line(image, tuple(landmark_point[17]), tuple(landmark_point[0]),
(255, 255, 255), 2)
# キーポイント
for index, landmark in enumerate(landmark_point):
if index == 0: # 手首1
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 1: # 手首2
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 2: # 親指:付け根
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 3: # 親指:第1関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 4: # 親指:指先
cv.circle(image, (landmark[0], landmark[1]), 8, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 8, (0, 0, 0), 1)
if index == 5: # 人差指:付け根
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 6: # 人差指:第2関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 7: # 人差指:第1関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 8: # 人差指:指先
cv.circle(image, (landmark[0], landmark[1]), 8, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 8, (0, 0, 0), 1)
if index == 9: # 中指:付け根
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 10: # 中指:第2関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 11: # 中指:第1関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 12: # 中指:指先
cv.circle(image, (landmark[0], landmark[1]), 8, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 8, (0, 0, 0), 1)
if index == 13: # 薬指:付け根
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 14: # 薬指:第2関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 15: # 薬指:第1関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 16: # 薬指:指先
cv.circle(image, (landmark[0], landmark[1]), 8, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 8, (0, 0, 0), 1)
if index == 17: # 小指:付け根
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 18: # 小指:第2関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 19: # 小指:第1関節
cv.circle(image, (landmark[0], landmark[1]), 5, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 5, (0, 0, 0), 1)
if index == 20: # 小指:指先
cv.circle(image, (landmark[0], landmark[1]), 8, (255, 255, 255),
-1)
cv.circle(image, (landmark[0], landmark[1]), 8, (0, 0, 0), 1)
return image
def draw_info(image, rowid, label):
cv.putText(image, "rowID(16frame):" + str(rowid), (10, 30), cv.FONT_HERSHEY_SIMPLEX,
1.0, (255, 255, 255), 2, cv.LINE_AA)
cv.putText(image, "GestureLabel:" + label, (10, 60), cv.FONT_HERSHEY_SIMPLEX,
1.0, (255, 255, 255), 2, cv.LINE_AA)
return image
if __name__ == '__main__':
main()