如何在 Python Linux 中使用内存映射文件
How To Use Memory Mapped File in Python Linux
正如我在 Python 文档中看到的那样,
https://docs.python.org/3/library/mmap.html.
Linux中的Python可以完全支持内存映射文件。然而,当我试图将这个想法应用到我的应用程序中时。我无法 运行 示例。
我的应用是将帧从 Python 文件(客户端)发送到另一个 Python 文件(服务器)。
客户代码
import mmap
import time
import os
import cv2 as cv
print("Opening camera...")
cap = cv.VideoCapture('/home/hunglv/Downloads/IMG_8442.MOV')
mm = None
try:
while True:
ret, img = cap.read()
if not ret:
break
if mm is None:
mm = mmap.mmap(-1,img.size,mmap.MAP_SHARED, mmap.PROT_WRITE)
# write image
start = time.time()
buf = img.tobytes()
mm.seek(0)
mm.write(buf)
mm.flush()
stop = time.time()
print("Writing Duration:", (stop - start) * 1000, "ms")
except KeyboardInterrupt:
pass
print("Closing resources")
cap.release()
mm.close()
服务器代码
import mmap
import time
import os
import cv2 as cv
import numpy as np
shape = (1080, 1920, 3)
n = np.prod(shape)
mm = mmap.mmap(-1, n)
while True:
# read image
print (mm)
start = time.perf_counter()
mm.seek(0)
buf = mm.read(12)
img = np.frombuffer(buf, dtype=np.uint8).reshape(shape)
stop = time.perf_counter()
print("Reading Duration:", (stop - start) * 1000, "ms")
cv.imshow("img", img)
key = cv.waitKey(1) & 0xFF
key = chr(key)
if key.lower() == "q":
break
cv.destroyAllWindows()
mm.close()
在服务器端,我将内存索引设置为0,并尝试从内存中读取字节。但是,似乎是服务端无法正确读取客户端的数据。
[更新]
我试图在服务器端读出前 12 个字节。该值是恒定的,不再改变。
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
此外,
随机帧的前 12 个字节是
b'\xf5\xff\xff\xf0\xfa\xfe\xdf\xe9\xed\xd2\xdc\xe0'
首先我找到了可能有效的示例,但它使用 tagName
(客户端和服务器相同),这意味着它仅适用于 Window:
接下来我找到了适用于 Linux:
的代码
Sharing Python data between processes using mmap.
它在磁盘上创建真实文件,将其大小调整为图像大小,然后在 mmap()
中使用其 fd
我使用网络摄像头进行测试。
服务器
import mmap
import time
import os
import cv2
print("Opening camera...")
cap = cv2.VideoCapture(0)
#print(cap.get(cv.CAP_PROP_FRAME_WIDTH)) # 640
#print(cap.get(cv.CAP_PROP_FRAME_HEIGHT)) # 480
shape = (480, 640, 3)
n = (480*640*3)
fd = os.open('/tmp/mmaptest', os.O_CREAT | os.O_TRUNC | os.O_RDWR)
#os.write(fd, b'\x00' * n) # resize file
os.truncate(fd, n) # resize file
mm = None
try:
while True:
ret, img = cap.read()
if not ret:
break
if mm is None:
mm = mmap.mmap(fd, n, mmap.MAP_SHARED, mmap.PROT_WRITE) # it has to be only for writing
# write image
start = time.perf_counter()
buf = img.tobytes()
mm.seek(0)
mm.write(buf)
mm.flush()
stop = time.perf_counter()
print("Writing Duration:", (stop - start) * 1000, "ms")
except KeyboardInterrupt:
pass
print("Closing resources")
cap.release()
mm.close()
客户端
import mmap
import time
import os
import cv2
import numpy as np
shape = (480, 640, 3)
n = (480*640*3)
fd = os.open('/tmp/mmaptest', os.O_RDONLY)
mm = mmap.mmap(fd, n, mmap.MAP_SHARED, mmap.PROT_READ) # it has to be only for reading
while True:
# read image
start = time.perf_counter()
mm.seek(0)
buf = mm.read(n)
img = np.frombuffer(buf, dtype=np.uint8).reshape(shape)
stop = time.perf_counter()
print("Reading Duration:", (stop - start) * 1000, "ms")
cv2.imshow("img", img)
key = cv2.waitKey(1) & 0xFF
key = chr(key)
if key.lower() == "q":
break
cv2.destroyAllWindows()
mm.close()
顺便说一句: 可能 mmap()
和 -1
(不在磁盘上创建文件)可以与线程(或分叉)一起工作,因为它们共享相同的内存.
正如我在 Python 文档中看到的那样,
https://docs.python.org/3/library/mmap.html.
Linux中的Python可以完全支持内存映射文件。然而,当我试图将这个想法应用到我的应用程序中时。我无法 运行 示例。
我的应用是将帧从 Python 文件(客户端)发送到另一个 Python 文件(服务器)。
客户代码
import mmap
import time
import os
import cv2 as cv
print("Opening camera...")
cap = cv.VideoCapture('/home/hunglv/Downloads/IMG_8442.MOV')
mm = None
try:
while True:
ret, img = cap.read()
if not ret:
break
if mm is None:
mm = mmap.mmap(-1,img.size,mmap.MAP_SHARED, mmap.PROT_WRITE)
# write image
start = time.time()
buf = img.tobytes()
mm.seek(0)
mm.write(buf)
mm.flush()
stop = time.time()
print("Writing Duration:", (stop - start) * 1000, "ms")
except KeyboardInterrupt:
pass
print("Closing resources")
cap.release()
mm.close()
服务器代码
import mmap
import time
import os
import cv2 as cv
import numpy as np
shape = (1080, 1920, 3)
n = np.prod(shape)
mm = mmap.mmap(-1, n)
while True:
# read image
print (mm)
start = time.perf_counter()
mm.seek(0)
buf = mm.read(12)
img = np.frombuffer(buf, dtype=np.uint8).reshape(shape)
stop = time.perf_counter()
print("Reading Duration:", (stop - start) * 1000, "ms")
cv.imshow("img", img)
key = cv.waitKey(1) & 0xFF
key = chr(key)
if key.lower() == "q":
break
cv.destroyAllWindows()
mm.close()
在服务器端,我将内存索引设置为0,并尝试从内存中读取字节。但是,似乎是服务端无法正确读取客户端的数据。
[更新] 我试图在服务器端读出前 12 个字节。该值是恒定的,不再改变。
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
此外, 随机帧的前 12 个字节是
b'\xf5\xff\xff\xf0\xfa\xfe\xdf\xe9\xed\xd2\xdc\xe0'
首先我找到了可能有效的示例,但它使用 tagName
(客户端和服务器相同),这意味着它仅适用于 Window:
接下来我找到了适用于 Linux:
的代码Sharing Python data between processes using mmap.
它在磁盘上创建真实文件,将其大小调整为图像大小,然后在 mmap()
fd
我使用网络摄像头进行测试。
服务器
import mmap
import time
import os
import cv2
print("Opening camera...")
cap = cv2.VideoCapture(0)
#print(cap.get(cv.CAP_PROP_FRAME_WIDTH)) # 640
#print(cap.get(cv.CAP_PROP_FRAME_HEIGHT)) # 480
shape = (480, 640, 3)
n = (480*640*3)
fd = os.open('/tmp/mmaptest', os.O_CREAT | os.O_TRUNC | os.O_RDWR)
#os.write(fd, b'\x00' * n) # resize file
os.truncate(fd, n) # resize file
mm = None
try:
while True:
ret, img = cap.read()
if not ret:
break
if mm is None:
mm = mmap.mmap(fd, n, mmap.MAP_SHARED, mmap.PROT_WRITE) # it has to be only for writing
# write image
start = time.perf_counter()
buf = img.tobytes()
mm.seek(0)
mm.write(buf)
mm.flush()
stop = time.perf_counter()
print("Writing Duration:", (stop - start) * 1000, "ms")
except KeyboardInterrupt:
pass
print("Closing resources")
cap.release()
mm.close()
客户端
import mmap
import time
import os
import cv2
import numpy as np
shape = (480, 640, 3)
n = (480*640*3)
fd = os.open('/tmp/mmaptest', os.O_RDONLY)
mm = mmap.mmap(fd, n, mmap.MAP_SHARED, mmap.PROT_READ) # it has to be only for reading
while True:
# read image
start = time.perf_counter()
mm.seek(0)
buf = mm.read(n)
img = np.frombuffer(buf, dtype=np.uint8).reshape(shape)
stop = time.perf_counter()
print("Reading Duration:", (stop - start) * 1000, "ms")
cv2.imshow("img", img)
key = cv2.waitKey(1) & 0xFF
key = chr(key)
if key.lower() == "q":
break
cv2.destroyAllWindows()
mm.close()
顺便说一句: 可能 mmap()
和 -1
(不在磁盘上创建文件)可以与线程(或分叉)一起工作,因为它们共享相同的内存.