def button_recognition_click(self):
descirptor_in_use = abs(self.fourier_result)
fd_test = np.zeros((1, 31))
temp = descirptor_in_use[1]
for k in range(1, len(descirptor_in_use)):
fd_test[0, k - 1] = int(100 * descirptor_in_use[k] / temp)
efd_test = np.zeros((1, 15))
for k in range(1, len(self.efd_result)):
temp = np.sqrt(self.efd_result[k][0]**2 + self.efd_result[k][1]**2
) + np.sqrt(self.efd_result[k][2]**2 +
self.efd_result[k][3]**2)
efd_test[0, k - 1] = (int(1000 * temp))
test_knn, test_svm = cf.test_fd(fd_test)
print("test_knn =", test_knn)
print("test_svm =", test_svm)
test_knn_efd, test_svm_efd = cf.test_efd(efd_test)
print("test_knn_efd =", test_knn_efd)
print("test_svm_efd =", test_svm_efd)
num = [0] * 11
num[test_knn[0]] += 1
num[test_svm[0]] += 1
num[test_knn_efd[0]] += 1
num[test_svm_efd[0]] += 1
res = -1
for i in range(1, 11):
if num[i] >= 2:
res = i
break
if res == 10:
res = 0
print(res)
self.label_show_recognition.setText(str(res))
def button_recognition_click(self):
descirptor_in_use = self.hog_result
fd_test = np.zeros((1, 70))
temp = descirptor_in_use[1]
for k in range(1, 70):
fd_test[0, k - 1] = int(100 * descirptor_in_use[k])
print("descirptor_in_use", fd_test)
test_svm = cf.test_fd(fd_test)
print("test_svm =", test_svm)
print(test_svm[0])
if test_svm[0] == 1:
self.label_show_recognition.setText("右")
elif test_svm[0] == 2:
self.label_show_recognition.setText("左")
elif test_svm[0] == 3:
self.label_show_recognition.setText("上")
else:
self.label_show_recognition.setText("下")
x0 -= 5
elif key == ord('q'):
break
elif key == ord('s'):
path = './' + 'image_example' + '/'
name = str(cnt)
cv2.imwrite(path + 'roi_sun.png', roi)
cnt += 1
#cv2.imwrite(path + name+'.png',ret)
elif key == ord('p'):
descirptor_in_use = abs(fourier_result)
fd_test = np.zeros((1, 31))
temp = descirptor_in_use[1]
for k in range(1, len(descirptor_in_use)):
fd_test[0, k - 1] = int(100 * descirptor_in_use[k] / temp)
efd_test = np.zeros((1, 15))
for k in range(1, len(efd_result)):
temp = np.sqrt(efd_result[k][0]**2 +
efd_result[k][1]**2) + np.sqrt(
efd_result[k][2]**2 + efd_result[k][3]**2)
efd_test[0, k - 1] = (int(1000 * temp))
test_knn, test_svm = cf.test_fd(fd_test)
print("test_knn =", test_knn)
print("test_svm =", test_svm)
test_knn_efd, test_svm_efd = cf.test_efd(efd_test)
print("test_knn_efd =", test_knn_efd)
print("test_svm_efd =", test_svm_efd)
cv2.imshow('frame', frame) #播放摄像头的内容
cap.release()
cv2.destroyAllWindows() #关闭所有窗口
if IS_SHOW_CV_WINDOW:
cv2.imshow("roi", roi) # 显示手势框图
cv2.imshow("frame", frame)
cv2.imshow("ret", ret)
key = cv2.waitKey(1) & 0xFF # 按键判断并进行一定的调整 # 按'q'键退出录像
if key == ord('q'):
break
descirptor_in_use = abs(fourier_result)
fd_test = np.zeros((1, 31))
temp = descirptor_in_use[1]
for k in range(1, len(descirptor_in_use)):
fd_test[0, k - 1] = int(100 * descirptor_in_use[k] / temp)
efd_test = np.zeros((1, 15))
for k in range(1, len(efd_result)):
temp = np.sqrt(efd_result[k][0]**2 +
efd_result[k][1]**2) + np.sqrt(efd_result[k][2]**2 +
efd_result[k][3]**2)
efd_test[0, k - 1] = (int(1000 * temp))
test_svm = cf.test_fd(fd_test)
test_svm_efd = cf.test_efd(efd_test)
print("test_svm:", test_svm[0], ", test_svm_efd:", test_svm_efd[0])
if len(test_svm) == 0 or len(test_svm_efd) == 0:
continue
#
cmd = int(test_svm)
if RASPI_OS:
scc.cmd_handle(cmd)
cap.release()
cv2.destroyAllWindows() # 关闭所有窗口