I am working on a project which I need to synthesize a video from existing frames and then format it exactly like a webcam device and make it available to external computers. In other words, this USB output should look exactly as if it was generated by a webcam. Can someone provide some hints about any existing library or any methodology to do this? The target system to create "webcam&quo
我正在研究一个项目，我需要从现有帧合成视频，然后将其格式化为网络摄像头设备，并将其提供给外部计算机。 换句话说，这个USB输出应该看起来就好像它是由网络摄像头产生的一样。 有人可以提供关于任何现有图书馆或任何方法的暗示吗？ 通过USB创建“网络摄像头”输出的目标系统是UBUNTU。 谢谢 通常通过库或操作系统访问网络摄像头，而不是低级别的USB设备。 在python中，阅读摄像头帧的选项是https://github.com/gebart/p
I'm currently trying to run a number of tests against a JSON string there are however a few difficulties that I am encountering. Here's what I have so far. class PinpyTests(jsonstr, campaign): data = json.loads(jsonstr) test = False def dwellTest(self): if self.data.get('dwellTime', None) is not None: if self.data.get('dwellTime') >= self.campaign.n
我目前正在尝试针对JSON字符串运行多个测试，但遇到了一些困难。 这是迄今为止我所拥有的。 class PinpyTests(jsonstr, campaign): data = json.loads(jsonstr) test = False def dwellTest(self): if self.data.get('dwellTime', None) is not None: if self.data.get('dwellTime') >= self.campaign.needed_dwellTime: # Result matches, dwell time test passed.
This question already has an answer here: What is tail recursion? 23 answers Well, let's look at a super simple function. def super_simple_function(): return 0 What happens when I do x = super_simple_function() ? >>> x = super_simple_function() >>> x 0 That's because the function's return value is zero. So there's a function object, which gives (retur
这个问题在这里已经有了答案： 什么是尾递归？ 23个答案 那么，让我们看看一个超级简单的功能。 def super_simple_function(): return 0 当我做x = super_simple_function()时会发生什么？ >>> x = super_simple_function() >>> x 0 这是因为函数的返回值为零。 所以有一个函数对象，它在被调用时给出（返回）一个值。 让我们一行一行看看递归函数。 想象一下，我们通过2和3作为参数，如下所示
I am trying to understand how python manages stack and heap. So I wanted to do some "bad" programming and cause a stack overflow and heap overflow. What I don't understand is why strings for example go to stack while all others go to heap. Is it just agreement of the designers? Are the examples correct? From what I have read everything in python is generated in heap since its o
我想了解python如何管理堆栈和堆。 所以我想做一些“不好”的编程，导致堆栈溢出和堆溢出。 我不明白的是为什么字符串例如在所有其他堆栈堆叠时堆叠起来。 这只是设计师的协议吗？ 这些例子是否正确？ 从我读过的所有东西都是在python中生成的，因为它的面向对象，对吧？ 编辑 ：我想像C这样的语言堆栈有一个固定的长度，但在python中，即使堆栈是动态分配的，正如Anycorn在他的回答中所说的。 这就是为什么我也得到完整的
I have taken Problem #12 from Project Euler as a programming exercise and to compare my (surely not optimal) implementations in C, Python, Erlang and Haskell. In order to get some higher execution times, I search for the first triangle number with more than 1000 divisors instead of 500 as stated in the original problem. The result is the following: C: lorenzo@enzo:~/erlang$ gcc -lm -o euler
我将Project Euler的问题＃12作为编程练习，并比较了C，Python，Erlang和Haskell中的我的（当然不是最优的）实现。 为了获得更高的执行时间，我搜索了第一个包含1000个以上除数的三角形数字，而不是原始问题中所述的500个。 结果如下： C： lorenzo@enzo:~/erlang$ gcc -lm -o euler12.bin euler12.c lorenzo@enzo:~/erlang$ time ./euler12.bin 842161320 real 0m11.074s user 0m11.070s sys 0m0.000s 蟒蛇： lor
What is the best way to represent and solve a maze given an image? Given an JPEG image (as seen above), what's the best way to read it in, parse it into some data structure and solve the maze? My first instinct is to read the image in pixel by pixel and store it in a list (array) of boolean values: True for a white pixel, and False for a non-white pixel (the colours can be discarded). The
代表和解决迷宫给出图像的最佳方式是什么？ 给出一个JPEG图像（如上所示），读入它的最佳方式是什么，将其解析为一些数据结构并解决迷宫问题？ 我的第一本能是以像素为单位读取图像并将其存储在布尔值列表（数组）中：对于白色像素为True ，对于非白色像素为False （可丢弃颜色）。 这种方法的问题是，图像可能不是“像素完美”。 我的意思是，如果在墙上某处有白色像素，它可能会产生一个无意的路径。 另一种方法（经过一
I always get confused with licenses, I'm reading up again, but I'm sure someone out there already understands this and may be able to explain it more clearly. I'm trying to get my company to use geodjango, and being a typical large enterprise company they don't want to open-source the resulting project. And therefore opposed to touching anything stamped "GPL". Looki
我总是对许可证感到困惑，我正在重新阅读，但我确定有人在那里已经理解了这一点，并且可以更清楚地解释它。 我试图让我的公司使用geodjango，并成为一家典型的大型企业公司，他们不希望开源项目。 因此，不要触摸任何盖有“GPL”的东西。 使用推荐的postgresql查看geodjango堆栈的许可证是： Django - BSD许可证 Postgresql - BSD许可证 PostGIS - GPL GEOS - LGPL PROJ.4 - MIT许可证 GDAL - MIT / X许可
Why is the Borg pattern better than the Singleton pattern? I ask because I don't see them resulting in anything different. Borg: class Borg: __shared_state = {} # init internal state variables here __register = {} def __init__(self): self.__dict__ = self.__shared_state if not self.__register: self._init_default_register() Singleton: class Singleton: def __init__
为什么Borg模式比Singleton模式更好？ 我问，因为我没有看到他们导致任何不同。 博格： class Borg: __shared_state = {} # init internal state variables here __register = {} def __init__(self): self.__dict__ = self.__shared_state if not self.__register: self._init_default_register() 辛格尔顿： class Singleton: def __init__(self): # init internal state variables here
I'm trying to create a static variable to be accessed through different classes, assigning value to it, and getting this value when needed. I did use this way in order to achieve this, and that leads me to including a property as following: class GetPartition(Partition): _i = 100 def __init__(self): super(Partition,self).__init__("get") def get_i(self): return ty
我试图创建一个静态变量，通过不同的类访问，赋值给它，并在需要时获取这个值。 为了实现这一目的，我确实使用了这种方式，这导致我包含一个属性如下： class GetPartition(Partition): _i = 100 def __init__(self): super(Partition,self).__init__("get") def get_i(self): return type(self)._i def set_i(self,val): type(self)._i = val i = property(get_i, set_i) 这是
Python gives us the ability to create 'private' methods and variables within a class by prepending double underscores to the name, like this: __myPrivateMethod() . How, then, can one explain this >>> class MyClass: ... def myPublicMethod(self): ... print 'public method' ... def __myPrivateMethod(self): ... print 'this is private!!' ... >>> obj = MyClass(
Python使我们能够在类中创建'private'方法和变量，方法是在名称前加双下划线，如下所示： __myPrivateMethod() 。 那么，如何解释呢？ >>> class MyClass: ... def myPublicMethod(self): ... print 'public method' ... def __myPrivateMethod(self): ... print 'this is private!!' ... >>> obj = MyClass() >>> obj.myPublicMethod() public method >>> obj.__myPrivateMethod() T