将一组处理过的图像保存在一个文件夹中
Saving an array of processed images in a folder
我有这个代码和这个函数dense_optical_flow
,它的输出是一个数组。
该数组的每个元素都是一个图像。如何将这些图片分别保存在一个文件夹中?
%pylab
import cv2
import glob
import matplotlib
import numpy
def dense_optical_flow(images):
assert len(images) > 1
ret = []
pt = 0
frame1 = cv2.imread(images[pt])
#print(frame1.shape)
prvs = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
pt += 1
while (pt != len(images)):
frame2 = cv2.imread(images[pt])
next = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(prvs, next,None, 0.5, 3, 15, 3, 5, 1.2, 0)
mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
hsv[..., 0] = ang * 180 / np.pi / 2
hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
ret.append(rgb)
prvs = next
pt += 1
return np.array(ret)
files = glob.glob("/home/roberto/workspace/TEST/INPUT/intest/*.png")
flist = sorted(files)
plt.imshow(dense_optical_flow(flist)[1]) #this line is just for test!
我已经像这样修改了循环
while (pt != len(images)):
frame2 = cv2.imread(images[pt])
next = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(prvs, next,None, 0.5, 3, 15, 3, 5, 1.2, 0)
mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
hsv[..., 0] = ang * 180 / np.pi / 2
hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
ret.append(rgb)
prvs = next
for image in ret:
filename = '/home/roberto/workspace/TEST/OUTPUT/fbtest/'
cv2.imwrite(filename + '_TEST' + image +'.npg', image )
pt += 1
return np.array(ret)
但是还是不正确!
错误:UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U48'), dtype('<U48')) -> dtype('<U48')
如评论所述,cv2.imwrite()
应该这样做:
for image in ret:
filename = xxx ## something that changes in this loop -> you can set a complete path to manage folders
cv2.imwrite(filename , image )
我有这个代码和这个函数dense_optical_flow
,它的输出是一个数组。
该数组的每个元素都是一个图像。如何将这些图片分别保存在一个文件夹中?
%pylab
import cv2
import glob
import matplotlib
import numpy
def dense_optical_flow(images):
assert len(images) > 1
ret = []
pt = 0
frame1 = cv2.imread(images[pt])
#print(frame1.shape)
prvs = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
pt += 1
while (pt != len(images)):
frame2 = cv2.imread(images[pt])
next = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(prvs, next,None, 0.5, 3, 15, 3, 5, 1.2, 0)
mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
hsv[..., 0] = ang * 180 / np.pi / 2
hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
ret.append(rgb)
prvs = next
pt += 1
return np.array(ret)
files = glob.glob("/home/roberto/workspace/TEST/INPUT/intest/*.png")
flist = sorted(files)
plt.imshow(dense_optical_flow(flist)[1]) #this line is just for test!
我已经像这样修改了循环
while (pt != len(images)):
frame2 = cv2.imread(images[pt])
next = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(prvs, next,None, 0.5, 3, 15, 3, 5, 1.2, 0)
mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
hsv[..., 0] = ang * 180 / np.pi / 2
hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
ret.append(rgb)
prvs = next
for image in ret:
filename = '/home/roberto/workspace/TEST/OUTPUT/fbtest/'
cv2.imwrite(filename + '_TEST' + image +'.npg', image )
pt += 1
return np.array(ret)
但是还是不正确!
错误:UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U48'), dtype('<U48')) -> dtype('<U48')
如评论所述,cv2.imwrite()
应该这样做:
for image in ret:
filename = xxx ## something that changes in this loop -> you can set a complete path to manage folders
cv2.imwrite(filename , image )