WebOct 16, 2024 · TypeError: new(): data must be a sequence (got float) @tengshaofeng Do you have an intuition about what am I doing wrong? I can also share my dataset rendering class. It has a getiitem method … WebFeb 20, 2024 · 1. Your data is a list, and in python there is no list * float operation defined (the only one defined is list * int, which creates copies of the list, rather than what you want which is multiplying each element of the list independently by the value of the int/float). What you want is to convert it to numpy array, where array * flat is a well ...
ValueError: setting an array element with a sequence
WebFeb 26, 2012 · If you want to convert (numpy.array OR numpy scalar OR native type OR numpy.darray) TO native type you can simply do : converted_value = getattr (value, "tolist", lambda: value) () tolist will convert your scalar or array to python native type. The default lambda function takes care of the case where value is already native. WebJan 27, 2024 · You have a numpy array and you want to create a pytorch tensor from it. You can use torch.from_numpy to achieve this. Note that torch.from_numpy expects an … slow dilation
VirConv/transforms.py at master · hailanyi/VirConv · GitHub
WebJul 5, 2015 · I think it is more useful, when debugging numpy code, to focus on getting the shapes right. As the accepted answer notes, this was bascially an array dimension issue. So I sprinkle my development code with print arr.shape like statements, or similar assert statements.dtype isn't as diagnositic. And type mainly helps distinguish lists from arrays. … WebMar 4, 2024 · brightness_factor (float): How much to adjust the brightness. Can be: any non negative number. 0 gives a black image, 1 gives the: original image while 2 increases the brightness by a factor of 2. Returns: PIL Image: Brightness adjusted image. """ if not _is_pil_image(img): raise TypeError('img should be PIL Image. Got {}'.format(type(img))) WebJul 4, 2024 · Yeah, you are right. You have to pass a valid np.array to the function, so. state = torch.from_numpy(np.array(state)) should work. slow digestive system and weight gain