-
Notifications
You must be signed in to change notification settings - Fork 1
/
minimap.py
255 lines (223 loc) · 9.31 KB
/
minimap.py
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
import math
import os
import cv2
import numpy as np
from utilities import get_screenshot, vector_angle, rotate_image
class MiniMap:
def __init__(self):
self.distance = None
self.current_path_fname = None
self.path_img_list = []
self.record_img_index = 1
self.record_distance = 8
self.path_img = None
self.anchors = []
self.orientation = None
self.magnitude = 3
self.move_angle = 0
self.center_point = (1818, 131)
self.minimap_half_size = 80
self.minimap_img_last_frame = None
self.minimap_img = None
self.draw_minimap = True
self.draw_minimap_img = None
self.save_path = "Path"
self.get_anchors()
def get_minimap(self):
bbox = (self.center_point[0] - self.minimap_half_size,
self.center_point[1] - self.minimap_half_size,
self.center_point[0] + self.minimap_half_size,
self.center_point[1] + self.minimap_half_size)
self.minimap_img = get_screenshot(bbox=bbox)
if self.minimap_img_last_frame is None:
self.minimap_img_last_frame = self.minimap_img
def get_anchors(self):
if self.minimap_img is None:
self.get_minimap()
shape = self.minimap_img.shape
points = [
(shape[0] / 2.0, shape[1] / 4.0),
(shape[0] / 4.0, shape[1] / 2.0),
(shape[0] / 4.0 * 3, shape[1] / 2.0),
(shape[0] / 2.0, shape[1] / 4.0 * 3)
]
for i in range(len(points)):
anchor = Anchor(self.minimap_img)
anchor.center = points[i]
anchor.id = i
self.anchors.append(anchor)
def get_target(self):
most_confidence = 0
angle = None
distance = None
for anchor in self.anchors:
anchor.minimap_img_last_frame = self.path_img
anchor.update_minimap_img(self.minimap_img)
anchor.get_target()
if anchor.confidence > most_confidence:
most_confidence = anchor.confidence
angle = anchor.move_angle
distance = anchor.distance
self.move_angle = int(angle)
self.distance = distance
def record_path(self, title="path"):
self.get_minimap()
if self.path_img is None:
self.path_img = self.minimap_img
name = title + "_0"
self.save_img(name)
print("Start record")
return
self.get_target()
if self.distance > self.record_distance:
self.path_img = self.minimap_img
name = title + "_" + str(self.record_img_index)
self.save_img(name)
print("recorded:", self.record_img_index)
self.record_img_index += 1
def get_orientation(self):
arrow = Arrow()
if self.minimap_img is None:
self.get_minimap()
arrow.minimap_img = self.minimap_img
arrow.get_template_arrow()
arrow.get_rotation()
self.orientation = arrow.orientation
def show_minimap(self):
if self.draw_minimap:
self.draw()
cv2.imshow('Computer Vision', self.draw_minimap_img)
else:
cv2.imshow('Computer Vision', self.minimap_img)
cv2.waitKey(1)
self.draw_minimap_img = None
def draw(self):
if self.draw_minimap_img is None:
self.draw_minimap_img = self.minimap_img.copy()
if self.distance is None:
return
self.get_orientation()
colors = ((255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 0, 255))
# draw orientation
orientation = "ori:" + str(self.orientation) + "\'"
org = (10, 40)
self.draw_minimap_img = cv2.putText(self.draw_minimap_img, orientation, org, cv2.FONT_HERSHEY_SIMPLEX, 0.4,
(255, 255, 255), 1, cv2.LINE_AA)
# draw distance
distance = "dis:" + str(int(self.distance))
org = (10, 140)
self.draw_minimap_img = cv2.putText(self.draw_minimap_img, distance, org, cv2.FONT_HERSHEY_SIMPLEX, 0.4,
(255, 255, 255), 1, cv2.LINE_AA)
# draw anchors rectangle
for i in range(len(self.anchors)):
anchor = self.anchors[i]
rec = anchor.rec
self.draw_minimap_img = cv2.rectangle(self.draw_minimap_img,
(rec[0], rec[2]), (rec[1], rec[3]),
colors[i], 1)
text = str(int(anchor.confidence * 100)) + "%"
org = (rec[0], rec[2])
self.draw_minimap_img = cv2.putText(self.draw_minimap_img, text, org, cv2.FONT_HERSHEY_SIMPLEX, 0.3,
(0, 255, 255), 1, cv2.LINE_AA)
def save_img(self, name):
if self.minimap_img is None:
self.get_minimap()
file_name = self.save_path + "/" + name + ".jpg"
cv2.imwrite(file_name, self.minimap_img)
def load_path_img(self, name):
try:
self.path_img = cv2.imread(self.save_path + "/" + name)
except:
self.path_img = cv2.imread(self.save_path + "/" + "path_0.jpg")
def load_next_path_img(self):
fname = self.current_path_fname[:-4]
fname, index = fname.split("_")
index = str(int(index) + 1)
self.current_path_fname = fname + "_" + index + ".jpg"
if not os.path.isfile(self.save_path + "/" + self.current_path_fname):
self.current_path_fname = fname + "_0.jpg"
self.load_path_img(self.current_path_fname)
print("next path:", self.current_path_fname)
def load_path_img_list(self):
for (dirpath, dirnames, filenames) in os.walk(self.save_path):
self.path_img_list.extend(filenames)
break
def find_closest_point(self):
self.load_path_img_list()
closest_point = {}
for img_file_name in self.path_img_list:
path_img = cv2.imread(self.save_path + "/" + img_file_name)
res = cv2.matchTemplate(self.minimap_img, path_img, cv2.TM_CCOEFF_NORMED)
confidence = np.max(res)
closest_point[img_file_name] = confidence
self.current_path_fname = max(closest_point, key=closest_point.get)
print("Found closest path:", self.current_path_fname)
def init_path(self):
# self.current_path_fname = "path_1.jpg"
self.find_closest_point()
self.load_path_img(self.current_path_fname)
class Anchor:
def __init__(self, minimap_img):
self.distance = 0
self.id = None
self.draw_minimap_img = None
self.confidence = None
self.center = None
self.move_angle = None
self.init_offset = None
self.is_drawing_rec = True
self.img = None
self.rec = None
self.anchors_half_size = 20
self.minimap_img = minimap_img
self.minimap_img_last_frame = minimap_img
def get_anchor_img(self):
center = self.center
x_start = int(center[0] - self.anchors_half_size)
x_end = int(center[0] + self.anchors_half_size)
y_start = int(center[1] - self.anchors_half_size)
y_end = int(center[1] + self.anchors_half_size)
self.img = self.minimap_img[y_start:y_end, x_start:x_end]
self.rec = [x_start, x_end, y_start, y_end]
def get_target(self):
self.get_anchor_img()
res = cv2.matchTemplate(self.minimap_img_last_frame, self.img, cv2.TM_CCOEFF_NORMED)
self.confidence = np.max(res)
offset = (cv2.minMaxLoc(res)[3][0], cv2.minMaxLoc(res)[3][1])
move = self.center[0] - offset[0] - self.anchors_half_size, self.center[1] - offset[1] - self.anchors_half_size
self.distance = math.sqrt(sum(v ** 2 for v in move))
self.move_angle = vector_angle((0, -1), move)
def update_minimap_img(self, minimap_img):
self.minimap_img = minimap_img
class Arrow:
def __init__(self):
self.orientation = None
self.player_arrow_img = None
self.template_arrow = None
self.minimap_img = None
self.template_arrow_path = "Source_img/PlayerTemplate.jpg"
self.player_arrow_size = 20
def get_template_arrow(self):
self.template_arrow = cv2.imread(self.template_arrow_path)
def get_player_arrow(self):
shape = self.minimap_img.shape
center = (shape[0] / 2, shape[1] / 2)
x_start = int(center[0] - (self.player_arrow_size / 2))
x_end = int(center[0] + (self.player_arrow_size / 2))
y_start = int(center[1] - (self.player_arrow_size / 2))
y_end = int(center[1] + (self.player_arrow_size / 2))
self.player_arrow_img = self.minimap_img[y_start:y_end, x_start:x_end]
def get_rotation(self):
self.get_player_arrow()
rotate_angle = [0, 0]
for i in range(0, 360):
rotated_template_arrow = rotate_image(self.template_arrow, i)
res = cv2.matchTemplate(rotated_template_arrow, self.player_arrow_img, cv2.TM_CCOEFF_NORMED)
confidence = np.max(res)
if confidence > rotate_angle[1]:
rotate_angle = [i, confidence]
self.orientation = rotate_angle[0]
pass
def show(self):
cv2.imshow('arrow', self.player_arrow_img)
cv2.waitKey(1)