temp_image是(600,600,3),取值范围从0到1。
def pro_process(temp_img, input_size):
img = np.asarray(temp_img).astype('float32')
img = np.array(Image.fromarray(img).resize((input_size, input_size)).convert(3))
return img
它会给出以下错误:
Traceback (most recent call last):
File "S:\Program Files\Python36\lib\site-packages\PIL\Image.py", line 2681, in fromarray
mode, rawmode = _fromarray_typemap[typekey]
KeyError: ((1, 1, 3), '<f4')
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "H:\OneDrive\synchronization code\Developing collection\Python\MNet_DeepCDR-master\mnet_deep_cdr_ide\run\Step_3_MNet_test.py", line 56, in <module>
temp_img = pro_process(Disc_flat, CDRSeg_size)
File "S:\Program Files\Python36\lib\site-packages\mnet_deep_cdr\mnet_utils.py", line 18, in pro_process
img = np.array(Image.fromarray(img).resize((input_size, input_size)).convert(3))
File "S:\Program Files\Python36\lib\site-packages\PIL\Image.py", line 2683, in fromarray
raise TypeError("Cannot handle this data type: %s, %s" % typekey)
TypeError: Cannot handle this data type: (1, 1, 3), <f4
项目链接:https://github.com/HzFu/MNet_DeepCDR
错误是什么?如何修复它?
根据这个链接:PIL TypeError: Cannot handle this data type我已经更新了我的代码,但仍然有一个错误
def pro_process(temp_img, input_size):
print(temp_img.shape)
img = np.asarray(temp_img).astype('float32')
img = np.array(Image.fromarray((img * 255).astype(np.uint8)).resize((input_size, input_size)).convert(3))
return img
错误:
Traceback (most recent call last):
File "H:\OneDrive\synchronization code\Developing collection\Python\MNet_DeepCDR-master\mnet_deep_cdr_ide\run\Step_3_MNet_test.py", line 56, in <module>
temp_img = pro_process(Disc_flat, CDRSeg_size)
File "S:\Program Files\Python36\lib\site-packages\mnet_deep_cdr\mnet_utils.py", line 18, in pro_process
img = np.array(Image.fromarray((img * 255).astype(np.uint8)).resize((input_size, input_size)).convert(3))
File "S:\Program Files\Python36\lib\site-packages\PIL\Image.py", line 995, in convert
im = self.im.convert(mode, dither)
TypeError: argument 1 must be str, not int
发布于 2020-07-10 23:08:20
错误消息似乎是在抱怨形状,但实际上是关于数据类型。乘以255,然后更改为uint8,为我解决了这个问题:
random_array = np.random.random_sample(content_array.shape) * 255
random_array = random_array.astype(np.uint8)
random_image = Image.fromarray(random_array)
发布于 2020-03-09 12:55:51
请尝试此代码:
np.array(Image.fromarray((img * 255).astype(np.uint8)).resize((input_size, input_size)).convert('RGB'))
发布于 2020-02-22 21:22:20
该问题与数组的浮点(0-1)类型有关。将数组转换为Uint (0-255)。以下线程是相关的:PIL TypeError: Cannot handle this data type
im = Image.fromarray((x * 255).astype(np.uint8))
https://stackoverflow.com/questions/60138697
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