Question

我已经使用Tensorflow实现了实时对象检测，并按照this post和this GitHub repo中所述打开了cv。

对象检测效果很好，但是我无法实现fps计算器。

这是我编写的代码：

import datetime


class FramesPerSecond:
    def __init__(self):
    self._startTime = None
    self._currentTime = None
    self._total_number_of_frames = 0

def start(self):
    # start timer
    self._startTime = datetime.datetime.now()
    return self

def stop(self):
    # stop times
    self._currentTime = datetime.datetime.now()

def update_frames(self):
    self._total_number_of_frames = self._total_number_of_frames + 1

def elapsed_time(self):
    return (datetime.datetime.now() - self._startTime).total_seconds()

def current_fps(self):
    return self._total_number_of_frames / self.elapsed_time()

current_fps会返回一个在整个流中增加的值，而不是重现在视频流的持续时间内保持不变的值。

Answer 1

您可以尝试类似的方法...尽管我不确定您是否确实想要这样或其他方法...

import datetime

class FPS:
    def __init__(self):
        ...
        ...
        self._elapsed = 0
        self._fps = 0

    def start(self, ttl):
        self._startTime = datetime.datetime.now()
        self._currentTime = datetime.datetime.now() + datetime.timedelta(seconds=ttl)
        # print('counter started at --> ', self._startTime)
        # print('counter stopped at --> ', self._currentTime)
        return self._startTime, self._currentTime

    def elapsed_time(self):
        self._elapsed = (self._currentTime - self._startTime).total_seconds()
        return self._elapsed

    def update_frames(self):
        curr, start = self._currentTime, self._startTime

        if curr != start and curr != 0:
            print('updatin frames ...')
            for i in range(int(self._elapsed) + 1):
                self._total_number_of_frames += i
        else:
            self._total_number_of_frames += 1

        self.current_fps()
        print("frames: {}, fps: {}, time spent: {}".format(
            self._total_number_of_frames,
            self._fps,
            self._elapsed
        ))

    def current_fps(self):
        self._fps = self._total_number_of_frames / self._elapsed
        return self._fps



if __name__ == '__main__':
    fps = FPS()
    ttl = int(input('time-to-live in seconds: '))
    fps.start(ttl)
    fps.elapsed_time()
    fps.update_frames()

Answer 2

current_fps函数返回一个随时间增加的值，因为self._total_number_of_frames属性将继续增加，而经过的时间将在循环的每次迭代中或多或少保持恒定。基本上，分子将永远增加，而分母将保持在一定范围内，从而导致该值随时间增加。

为避免此问题，我们必须允许经过的时间函数随着增加的帧而扩大，或者使用其他常数来衡量fps。让我们与后者一起使用，并保留一个单独的计数器变量。

因此，您的上述代码可以这样重写：

import time  # The time module is easier for our purpose.


class FramesPerSecond:
    def __init__(self):
        self.startTime = None
        self.total_number_of_frames = 0
        self.counter = 0
        self.frameRate = 1  # The number of seconds to wait for each measurement.

    def start(self):
        self.startTime = time.time()  # Returns a UNIX timestamp.

    def update_frames(self):
        self.total_number_of_frames += 1

    def elapsed_time(self):
        return time.time() - self.startTime

    def current_fps(self):
        return self.counter / self.elapsed_time()  # We are measuring against the counter instead of no. of frames.


fps = FramesPerSecond()
fps.start()

while True:  # Your main loop.

    # Rest of your code here #
    fps.update_frames()

    fps.counter += 1  # Count will increase until the if condition executes.
    if fps.elapsed_time() > fps.frameRate:  # We measure the fps only after 1 second has passed.
        print("FPS: ", fps.current_fps()) # The frames per second. 
        fps.counter = 0  # reset the counter for next iteration.
        fps.start()  # reset the start time.

希望这会有所帮助！

无法计算输出视频流的fps

2 个答案: