我用python编写了一些代码来打开USB摄像头并从中抓取帧。我对http流使用我的代码。对于JPEG编码,我使用lib涡轮JPEG库。为此,我使用64位操作系统。
product: Raspberry Pi 3 Model B Rev 1.2
serial: 00000000f9307746
width: 64 bits
capabilities: smp cp15_barrier setend swp我用不同的决心做了一些测试。
Resolution FPS Time for encode
640 x 480 ~35 ~0.01
1280 x 720 ~17 ~0.028这是我的密码
import time
import os
import re
import uvc
from turbojpeg import TurboJPEG, TJPF_GRAY, TJSAMP_GRAY
jpeg = TurboJPEG("/opt/libjpeg-turbo/lib64/libturbojpeg.so")
camera = None
import numpy as np
from threading import Thread
class ProcessJPG(Thread):
def __init__(self, data):
self.jpeg_data = None
self.data = data
super(ProcessJPG, self).__init__()
def run(self):
self.jpeg_data = jpeg.encode((self.data))
def get_frame(self):
self.frame = camera.get_frame()
global camera
dev_list = uvc.device_list()
print("devices: ", dev_list)
camera = uvc.Capture(dev_list[1]['uid'])
camera.frame_size = camera.frame_sizes[2] // set 1280 x 720
camera.frame_rate = camera.frame_rates[0] // set 30 fps
class GetFrame(Thread):
def __init__(self):
self.frame = None
super(GetFrame, self).__init__()
def run(self):
self.frame = camera.get_frame()
_fps = -1
count_to_fps = 0
_real_fps = 0
from time import time
_real_fps = ""
cfps_time = time()
while True:
if camera:
t = GetFrame()
t.start()
t.join()
img = t.frame
timestamp = img.timestamp
img = img.img
ret = 1
t_start = time()
t = ProcessJPG(img)
t.start()
t.join()
jpg = t.jpeg_data
t_end = time()
print(t_end - t_start)
count_to_fps += 1
if count_to_fps >= _fps:
t_to_fps = time() - cfps_time
_real_fps = 1.0 / t_to_fps
cfps_time = time()
count_to_fps = 0
print("FPS, ", _real_fps)编码线是:jpeg.encode((self.data))
我的问题是,它的是可以提高FPS 1280 x 720 (例如30 FPS)分辨率,还是我应该使用更强大的设备?当我在计算过程中查看htop时,CPU不会在100%中使用。
编辑:相机格式:
[video4linux2,v4l2 @ 0xa705c0] Raw : yuyv422 : YUYV 4:2:2 : 640x480 1280x720 960x544 800x448 640x360 424x240 352x288 320x240 800x600 176x144 160x120 1280x800
[video4linux2,v4l2 @ 0xa705c0] Compressed: mjpeg : Motion-JPEG : 640x480 1280x720 960x544 800x448 640x360 800x600 416x240 352x288 176x144 320x240 160x120

发布于 2019-04-24 18:53:23
这是可能的,你不需要更强大的硬件。
* Capture instance will always grab mjpeg conpressed frames from cameras.
当您的代码访问.img属性时,调用jpeg2yuv (请参阅这里和这里)。然后您将使用jpeg_encode()重新编码。在捕获之后尝试使用frame.jpeg_buffer,完全不要碰.img。
我看了一下带有RPi2的罗技C310上的pyuvc,并做了一个简化的例子,
import uvc
import time
def main():
dev_list = uvc.device_list()
cap = uvc.Capture(dev_list[0]["uid"])
cap.frame_mode = (1280, 720, 30)
tlast = time.time()
for x in range(100):
frame = cap.get_frame_robust()
jpeg = frame.jpeg_buffer
print("%s (%d bytes)" % (type(jpeg), len(jpeg)))
#img = frame.img
tnow = time.time()
print("%.3f" % (tnow - tlast))
tlast = tnow
cap = None
main()我每帧得到.033 s,在8%的CPU下计算到~30 CPU。如果我取消对#img = frame.img行的注释,在99%的CPU上,它会上升到~.054 s/帧或~18 CPU(解码时间限制了捕获率)。
https://stackoverflow.com/questions/55588207
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