这就是我通常用来将数据库中存储的图像转换为Python中的OpenCV图像的方式。@H_419_1@
import numpy as np
import cv2
from cv2 import cv
# Load image as string from file/database
fd = open('foo.jpg')
img_str = fd.read()
fd.close()
# CV2
nparr = np.fromstring(img_str, np.uint8)
img_np = cv2.imdecode(nparr, cv2.CV_LOAD_IMAGE_COLOR) # cv2.IMREAD_COLOR in OpenCV 3.1
# CV
img_ipl = cv.CreateImageHeader((img_np.shape[1], img_np.shape[0]), cv.IPL_DEPTH_8U, 3)
cv.SetData(img_ipl, img_np.tostring(), img_np.dtype.itemsize * 3 * img_np.shape[1])
# check types
print type(img_str)
print type(img_np)
print type(img_ipl)
我已添加了从numpy.ndarray到的转换cv2.cv.iplimage，因此上面的脚本将显示：@H_419_1@
<type 'str'>
<type 'numpy.ndarray'>
<type 'cv2.cv.iplimage'>
从最新的numpy开始1.18.5 +，np.fromstring发出警告，因此np.frombuffer应在该位置使用。@H_419_1@
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