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，我的程序因错误而终止：

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，该代码有效。 这看起来有点像here 描述的行为，但我使用的是更新版本的 OpenCV，所以可能还有其他事情发生？

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 DTrees 需要显式配置 - 如果您这样做 print(model_dtree.getMaxDepth())，它会返回 2147483647，这是 32 位有符号整数 (https://en.wikipedia.org/wiki/2,147,483,647) 的最大值。当您显式设置深度时，脚本运行成功：

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 2147483647, which we don't want
model_dtree.setMaxDepth(10) # set it to something reasonable
model_dtree.train(samples=samples, layout=cv2.ml.ROW_SAMPLE, responses=labels)
print('finished training!')