python opencv DTree模型：train（）以std :: length_error终止

Question

我正在使用opencv-python 4.2.0.32和Python 3.7.4。

当我在DTree模型上调用train（）时，我的程序终止并出现错误：

terminate called after throwing an instance of 'std::length_error'
  what():  vector::reserve
Aborted (core dumped)

当我使用KNearest模型而不是DTree时，代码起作用。看起来有点像here中描述的行为，但是我使用的是OpenCV的最新版本，所以也许还有其他情况吗？

重现行为的代码示例：

import numpy as np
import cv2

samples = np.ndarray((5, 2), np.float32)
labels = np.zeros((5, 1), dtype=np.float32)

# This works
model_knn = cv2.ml.KNearest_create()
model_knn.train(samples=samples, layout=cv2.ml.ROW_SAMPLE, responses=labels)

# This terminates with an error
model_dtree = cv2.ml.DTrees_create()
model_dtree.train(samples=samples, layout=cv2.ml.ROW_SAMPLE, responses=labels)

Answer 1

看起来像DTree，需要显式配置-如果执行print(model_dtree.getMaxDepth())，它将返回2147483647。当您明确设置深度时，脚本将成功运行：

import numpy as np
import cv2

samples = np.ndarray((5, 2), np.float32)
labels = np.zeros((5, 1), dtype=np.float32)

print(samples)
# This works
model_knn = cv2.ml.KNearest_create()
model_knn.train(samples=samples, layout=cv2.ml.ROW_SAMPLE, responses=labels)

# This terminates with an error
model_dtree = cv2.ml.DTrees_create()
print(model_dtree.getMaxDepth()) # should be some very high, nonsensical value
model_dtree.setMaxDepth(10) # set it to something reasonable
model_dtree.train(samples=samples, layout=cv2.ml.ROW_SAMPLE, responses=labels)
print('finished')