def pic_locate(pic_match,pic_origin,thresh,findall=True,rgb_bool=True): #pic_match is the dir path, pic_origin is the data array
"""
:param pic_match: 源图像路径或图像数组
:param pic_origin: 背景图像，ndarray
:param thresh: 阈值，数值
:param findall: true 为寻找全部匹配图像，false为只返回一个
:param rgb_bool: true为匹配颜色，false为不匹配颜色
:return:
"""
if(isinstance(pic_match,str)): #若为路径，则根据当前分辨率动态调整实际对比图像
pic_test = Image.open(pic_match,'r')
resolution = globalvar.get_window_resolution()
max_resolution = globalvar.get_max_resolution()
width = int(resolution[0] / max_resolution[0] * pic_test.size[0])
height = int(resolution[1] / max_resolution[1] * pic_test.size[1])
pic_test = np.array(pic_test.resize((width, height), Image.ANTIALIAS))
elif(isinstance(pic_match,np.ndarray)):
pic_test = pic_match
if findall:
position = aircv.find_all_template(pic_origin,pic_test,thresh,rgb=rgb_bool)
else:
position = aircv.find_template(pic_origin, pic_test, thresh,rgb=rgb_bool)
# C = np.fft.ifft2(np.fft.fft2(pic_origin)*fftpack.fft2(pic_match_path,(888,1435,3)))
return position
def pic_load_ram():
#must run after getting handle, when dealing with the pics which resolutions lower than the current one,
# the function should remove these pics which may cause unpredictable errors
window_resolution = globalvar.get_window_resolution()
max_resolution = globalvar.get_max_resolution()
if window_resolution[0] == 0:
raise Exception("未检测到模拟器")
for keys, pic_path in pic_confirm.items():
temp_im = pic_resize(pic_path, window_resolution,
pic_confirm_res[keys])
pic_confirm[keys] = np.array(temp_im)
for keys, pic_path in huodong_pic.items():
temp_im = pic_resize(pic_path, window_resolution,
huodong_pic_res[keys])
huodong_pic[keys] = np.array(temp_im)
for keys, pic_path in pic_where.items():
temp_im = pic_resize(pic_path, window_resolution, pic_where_res[keys])
pic_where[keys] = np.array(temp_im)
for keys, pic_path in staff_pic.items():
temp_im = pic_resize(pic_path, window_resolution, staff_pic_res[keys])
staff_pic[keys] = np.array(temp_im)
for keys, pic_path in guanqia_pic.items():
temp_im = pic_resize(pic_path, window_resolution,
guanqia_pic_res[keys])
guanqia_pic[keys] = np.array(temp_im)
#常量点 自定义分辨率适应
for keys, values in points.items():
if isinstance(values[0], int):
width = int(window_resolution[0] / max_resolution[0] * values[0])
height = int(window_resolution[1] / max_resolution[1] * values[1])
points[keys] = [width, height]
else:
for index, value_temp in enumerate(values):
width = int(window_resolution[0] / max_resolution[0] *
value_temp[0])
height = int(window_resolution[1] / max_resolution[1] *
value_temp[1])
values[index] = [width, height]
points[keys] = values
def get_score(self,event):
# if self.handle==None:
# self.handle = get_handle()
# im = prtsc(self.handle)
if isinstance(self.origin_img,np.ndarray) and isinstance(self.cut_img,np.ndarray):
pass
else:
wx.MessageBox("请先载入并裁剪相应图像")
return
im = self.origin_img
#changed to BGR aligned to the cv2
#im = im [:,:,::-1]
window_resolution = globalvar.get_window_resolution()
max_resolution = self.origin_res
match_im = config_ark.pic_resize(self.cut_img,window_resolution,max_resolution)
results = pic_locate(match_im,im,0.8,True,True)
if results:
for i in results:
pos = i['rectangle'][0]
width = i['rectangle'][2][0] - i['rectangle'][0][0]
height = i['rectangle'][1][1] - i['rectangle'][0][1]
# Draw the bounding rectangle
#self.rect = Rectangle((0, 0), 0, 0, facecolor='None', edgecolor='red')
#self.axes.add_patch(self.rect)
tmp_rect = Rectangle((0, 0), 0, 0, facecolor='None', edgecolor='red')
tmp_rect.set_width(width)
tmp_rect.set_height(height)
tmp_rect.set_xy(pos)
self.axes.add_patch(tmp_rect)
#tmp_rect.remove()
self.draws.append(tmp_rect)
#self.text = plt.text(pos[0],pos[1],"{0:.4f}".format(i['confidence']))
tmp_text = self.axes.text(pos[0],pos[1],"{0:.3f}".format(i['confidence']),fontdict={'color':'red','size':12},
bbox=dict(facecolor='white', alpha=0.8))
#tmp_text.remove()
self.draws.append(tmp_text)
self.canvas.draw()
for j in self.draws:
j.remove()
self.draws = []
else:
wx.MessageBox("模拟器中没有包含所选图像")
def get_score(self, event):
# if self.handle==None:
# self.handle = get_handle()
# im = prtsc(self.handle)
if isinstance(self.origin_img, np.ndarray) and isinstance(
self.cut_img, np.ndarray):
pass
else:
wx.MessageBox("请先载入并裁剪相应图像")
return
im = self.origin_img
#changed to BGR aligned to the cv2
#im = im [:,:,::-1]
window_resolution = globalvar.get_window_resolution()
max_resolution = self.origin_res
match_im = config_ark.pic_resize(self.cut_img, window_resolution,
max_resolution)
# str_results = pytesseract.image_to_string(match_im,lang='eng')
# point1, point2, point3, point4 = config_ark.baitan_price
# im_crop = im[point2 - config_ark.ymjh_pc_shift[1]:point4 - config_ark.ymjh_pc_shift[1], point1 - config_ark.ymjh_pc_shift[0]:point3 - config_ark.ymjh_pc_shift[0], :]
# thresh = [[220,255], [220,255], [220,255]] # RGB
# im_gray = cv2.cvtColor(im_crop.copy(), cv2.COLOR_BGR2GRAY)
# im_thresh = threshhold(im_crop, thresh)
# im_thresh = cv2.cvtColor(im_thresh.copy(), cv2.COLOR_BGR2GRAY)
# kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
# # im_dilated = cv2.dilate(im_thresh, (3, 3))
# im_erode = cv2.erode(im_thresh, kernel)
# # cv2.imshow("123", im_crop)
# # cv2.waitKey()
# results = cfs(im_erode)
# value_result = 0
# for rect in results:
# roi1 = im_gray[:, rect[0]:rect[1]]
# # roi = np.transpose(roi,(1,0))
# roi = fillout(roi1)
# if isinstance(roi, np.ndarray) == False:
# continue
# roi_hog_fd = hog(roi.copy(), orientations=9, pixels_per_cell=(14, 14), cells_per_block=(1, 1),
# visualise=False)
# roi_hog_fd = self.pp.transform(np.array([roi_hog_fd], 'float64'))
# nbr = self.clf.predict(roi_hog_fd)
# value_result = value_result * 10
# value_result += int(nbr[0])
# save_digits(roi,int(nbr[0]))
# # cv2.imshow("123",roi1)
# # cv2.waitKey()
# print(value_result)
point1, point2, point3, point4 = config_ark.yinliang_pos
im_crop = im[point2 - config_ark.ymjh_pc_shift[1]:point4 -
config_ark.ymjh_pc_shift[1],
point1 - config_ark.ymjh_pc_shift[0]:point3 -
config_ark.ymjh_pc_shift[0], :]
thresh = [[120, 200], [120, 200], [120, 200]] # RGB
im_gray = cv2.cvtColor(im_crop.copy(), cv2.COLOR_BGR2GRAY)
im_thresh = threshhold(im_crop.copy(), thresh)
im_thresh = cv2.cvtColor(im_thresh.copy(), cv2.COLOR_BGR2GRAY)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
# im_dilated = cv2.dilate(im_thresh, (3, 3))
im_erode = cv2.erode(im_thresh, kernel)
cv2.imshow("123", im_thresh)
cv2.waitKey()
results = cfs(im_erode)
value_result = 0
for rect in results:
roi1 = im_gray[rect[2]:rect[3], rect[0]:rect[1]]
# roi = np.transpose(roi,(1,0))
roi = fillout(roi1)
if isinstance(roi, np.ndarray) == False:
continue
roi_hog_fd = hog(roi.copy(),
orientations=9,
pixels_per_cell=(14, 14),
cells_per_block=(1, 1),
visualise=False)
roi_hog_fd = self.pp.transform(np.array([roi_hog_fd], 'float64'))
nbr = self.clf.predict(roi_hog_fd)
value_result = value_result * 10
value_result += int(nbr[0])
save_digits(roi, int(nbr[0]))
# cv2.imshow("123",roi1)
# cv2.waitKey()
print("当前银两{}".format(value_result))
self.scoreText8.SetLabel("{}".format(value_result))
results = pic_locate(match_im, im, 0.8, True, True)
if results:
for i in results:
pos = i['rectangle'][0]
width = i['rectangle'][2][0] - i['rectangle'][0][0]
height = i['rectangle'][1][1] - i['rectangle'][0][1]
# Draw the bounding rectangle
#self.rect = Rectangle((0, 0), 0, 0, facecolor='None', edgecolor='red')
#self.axes.add_patch(self.rect)
tmp_rect = Rectangle((0, 0),
0,
0,
facecolor='None',
edgecolor='red')
tmp_rect.set_width(width)
tmp_rect.set_height(height)
tmp_rect.set_xy(pos)
self.axes.add_patch(tmp_rect)
#tmp_rect.remove()
self.draws.append(tmp_rect)
#self.text = plt.text(pos[0],pos[1],"{0:.4f}".format(i['confidence']))
tmp_text = self.axes.text(pos[0],
pos[1],
"{0:.3f}".format(i['confidence']),
fontdict={
'color': 'red',
'size': 12
},
bbox=dict(facecolor='white',
alpha=0.8))
#tmp_text.remove()
self.draws.append(tmp_text)
self.canvas.draw()
for j in self.draws:
j.remove()
self.draws = []
else:
wx.MessageBox("模拟器中没有包含所选图像")
def pic_load_ram():
#must run get handle first
window_resolution = globalvar.get_window_resolution()
max_resolution = globalvar.get_max_resolution()
if window_resolution[0] == 0:
raise Exception("未检测到模拟器")
for keys, pic_path in config_ark.pic_confirm.items():
temp_im = Image.open(pic_path)
temp_im = temp_im.convert("RGB")
width = int(window_resolution[0] / max_resolution[0] * temp_im.size[0])
height = int(window_resolution[1] / max_resolution[1] *
temp_im.size[1])
temp_im = temp_im.resize((width, height), Image.ANTIALIAS)
config_ark.pic_confirm[keys] = np.array(temp_im)
for keys, pic_path in config_ark.pic_huodong.items():
temp_im = Image.open(pic_path)
temp_im = temp_im.convert("RGB")
width = int(window_resolution[0] / max_resolution[0] * temp_im.size[0])
height = int(window_resolution[1] / max_resolution[1] *
temp_im.size[1])
temp_im = temp_im.resize((width, height), Image.ANTIALIAS)
config_ark.pic_huodong[keys] = np.array(temp_im)
for keys, pic_path in config_ark.pic_where.items():
temp_im = Image.open(pic_path)
temp_im = temp_im.convert("RGB")
width = int(window_resolution[0] / max_resolution[0] * temp_im.size[0])
height = int(window_resolution[1] / max_resolution[1] *
temp_im.size[1])
temp_im = temp_im.resize((width, height), Image.ANTIALIAS)
config_ark.pic_where[keys] = np.array(temp_im)
for keys, pic_path in config_ark.staff_pic.items():
temp_im = Image.open(pic_path)
temp_im = temp_im.convert("RGB")
width = int(window_resolution[0] / max_resolution[0] * temp_im.size[0])
height = int(window_resolution[1] / max_resolution[1] *
temp_im.size[1])
temp_im = temp_im.resize((width, height), Image.ANTIALIAS)
config_ark.staff_pic[keys] = np.array(temp_im)
for keys, pic_path in config_ark.guanqia_pic.items():
temp_im = Image.open(pic_path)
temp_im = temp_im.convert("RGB")
width = int(window_resolution[0] / max_resolution[0] * temp_im.size[0])
height = int(window_resolution[1] / max_resolution[1] *
temp_im.size[1])
temp_im = temp_im.resize((width, height), Image.ANTIALIAS)
config_ark.guanqia_pic[keys] = np.array(temp_im)
#常量点 自定义分辨率适应
for keys, values in config_ark.points.items():
if isinstance(values[0], int):
width = int(window_resolution[0] / max_resolution[0] * values[0])
height = int(window_resolution[1] / max_resolution[1] * values[1])
config_ark.points[keys] = [width, height]
else:
for index, value_temp in enumerate(values):
width = int(window_resolution[0] / max_resolution[0] *
value_temp[0])
height = int(window_resolution[1] / max_resolution[1] *
value_temp[1])
values[index] = [width, height]
config_ark.points[keys] = values