Question

我正在使用带有picamera和opencv python模块的raspberry pi尝试进行一些快速捕获和处理。目前我正在使用http://picamera.readthedocs.org/en/latest/recipes2.html#rapid-capture-and-processing中的配方将每个图像捕获到BytesIO流。然后我在ImageProccessor类中添加了代码，将每个流转换为opencv对象并“动态”进行一些分析。

我当前的代码看起来像是：

import io
import time
import threading
import picamera
import cv2
import picamera.array
import numpy as np


# Create a pool of image processors
done = False
lock = threading.Lock()
pool = []

class ImageProcessor(threading.Thread):
    def __init__(self):
        super(ImageProcessor, self).__init__()
        self.stream = io.BytesIO()
        self.event = threading.Event()
        self.terminated = False
        self.start()

    def run(self):
        # This method runs in a separate thread
        global done
        while not self.terminated:
            # Wait for an image to be written to the stream
            if self.event.wait(1):
                try:
                    self.stream.seek(0)
                    # Read the image and do some processing on it
                    # Construct a numpy array from the stream
                    data = np.fromstring(self.stream.getvalue(), dtype=np.uint8)
                    # "Decode" the image from the array, preserving colour
                    image = cv2.imdecode(data, 1)

                    # Here goes more opencv code doing image proccessing

                    # Set done to True if you want the script to terminate
                    # at some point
                    #done=True
                finally:
                    # Reset the stream and event
                    self.stream.seek(0)
                    self.stream.truncate()
                    self.event.clear()
                    # Return ourselves to the pool
                    with lock:
                        pool.append(self)

def streams():
    while not done:
        with lock:
            if pool:
                processor = pool.pop()
            else:
                processor = None
        if processor:
            yield processor.stream
            processor.event.set()
        else:
            # When the pool is starved, wait a while for it to refill
            print ("Waiting")            
            time.sleep(0.1)

with picamera.PiCamera() as camera:
    pool = [ImageProcessor() for i in range(4)]
    camera.resolution = (640, 480)
    camera.framerate = 30
    camera.start_preview()
    time.sleep(2)
    camera.capture_sequence(streams(), use_video_port=True)

# Shut down the processors in an orderly fashion
while pool:
    with lock:
        processor = pool.pop()
    processor.terminated = True
    processor.join()

问题在于这涉及每个图像的JPEG编码和解码，这是有损耗且耗时的。建议的替代方案是捕获到picamera.array：http://picamera.readthedocs.org/en/latest/recipes1.html#capturing-to-an-opencv-object，对于单个图像代码：

import time
import picamera
import picamera.array
import cv2

with picamera.PiCamera() as camera:
    camera.start_preview()
    time.sleep(2)
    with picamera.array.PiRGBArray(camera) as stream:
        camera.capture(stream, format='bgr')
        # At this point the image is available as stream.array
        image = stream.array

效果很好，但我不知道如何组合这两段代码，以便ImageProcessor类定义picamera.array而不是BytesIO流。需要使用“with”语句为picamera.array生成流会让我感到困惑（我是python ...;）的新手）。谢谢你的任何指示。天使

Answer 1

我发现你可以从picamera模块中引用来源。

def raw_resolution(resolution):
    """
    Round a (width, height) tuple up to the nearest multiple of 32 horizontally
    and 16 vertically (as this is what the Pi's camera module does for
    unencoded output).
    """
    width, height = resolution
    fwidth = (width + 31) // 32 * 32
    fheight = (height + 15) // 16 * 16
    return fwidth, fheight


def bytes_to_rgb(data, resolution):
    """
    Converts a bytes objects containing RGB/BGR data to a `numpy`_ array.
    """
    width, height = resolution
    fwidth, fheight = raw_resolution(resolution)
    if len(data) != (fwidth * fheight * 3):
        raise PiCameraValueError(
            'Incorrect buffer length for resolution %dx%d' % (width, height))
    # Crop to the actual resolution
    return np.frombuffer(data, dtype=np.uint8).\
            reshape((fheight, fwidth, 3))[:height, :width, :]

您可以通过致电转换

image = bytes_to_rgb(self.stream.getvalue(),resolution)

其中分辨率为（宽度，高度）。 camera传递给PiRGBArray的原因是能够参考相机的分辨率。

使用＆＃34;和＆＃34;在python + picamera + opencv中的一个线程内

1 个答案: