NanjingForestryUniversity/supermachine-wood
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fix: 现场版本，修改了亮度排序和修改为选取亮度大于40的像素点

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duanmu 2023-05-28 11:11:10 +08:00
parent 7a5479504c
commit ef4b6b109f
1 changed files with 9 additions and 7 deletions
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16
classifer.py
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@ -301,7 +301,7 @@ class WoodClass(object):
x = cv2.cvtColor(x, cv2.COLOR_BGR2LAB)
x = np.concatenate((x, x_hsv), axis=2)
x = np.reshape(x, (x.shape[0] * x.shape[1], x.shape[2]))
x = x[x[:, 0] > 30]
x = x[x[:, 0] > 40]
# x = x[np.argsort(x[:, 0])]
# x = x[-self.k:, :]
@ -474,12 +474,13 @@ class WoodClass(object):
middle_num = len(x_data[y_data == 1])
light_num = len(x_data[y_data == 2])
# 将数据按照亮度进行排序
x_data = x_data[np.argsort(x_data[:, 0])]
# 按照x的顺序，将y和names也进行排序
y_data = y_data[np.argsort(x_data[:, 0])]
# 按照x的顺序，将img_names也进行排序，但是这里需要注意，img_names是一个list，所以需要先转换成np.array
img_names = [img_names[i] for i in np.argsort(x_data[:, 0])]
# x_data_sort = x_data[np.argsort(x_data[:, 0])]
# # 按照x的顺序，将y和names也进行排序
# y_data = y_data[np.argsort(x_data[:, 0])]
# # 按照x的顺序，将img_names也进行排序，但是这里需要注意，img_names是一个list，所以需要先转换成np.array
# img_names = [img_names[i] for i in np.argsort(x_data[:, 0])]
tmp = np.arange(0, 90)
tmp = tmp[np.argsort(x_data[:, 0])]
# 创建一个labels，用于存储每个像素点的标签
labels = np.zeros_like(x_data[:, 0])
# 将亮度最低的dark_num个像素点标记为0
@ -488,6 +489,7 @@ class WoodClass(object):
labels[-light_num:] = 2
# 将中间的middle_num个像素点标记为1
labels[dark_num:-light_num] = 1
labels = labels[np.argsort(tmp)]
if plot_2d:
plt.figure()
plt.scatter(x_data[:, 0], x_data[:, 1], c=labels)