🔒 image lists not working with numpy

[dim meteor]

test = cv2.imread("breast-hispathology-images/8863/0/8863_idx5_x51_y1251_class0.png",cv2.IMREAD_COLOR)

resized = cv2.resize(test, (50,50), interpolation=cv2.INTER_LINEAR)

img_arrays = [[resized, 0]]
np.shape(img_arrays)

returns:

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (1, 2) + inhomogeneous part

[stable sand]

@dim meteor

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[fierce pelican]

Last line, you prob want shape of resized

[dim meteor]

its 50, 50, 3

(50, 50, 3)*

should i just do it with a np array

[fierce pelican]

I don’t get the [[resized,0]]

Why a list of resized and 0?

[dim meteor]

0 is the label

that it is non-canceroud

and the double list is coz its a 2D array

in the previous function

[fierce pelican]

So your inhomogrnous problem is that you have a list of lists with a label and an image

Get rid of the label

[dim meteor]

but i need the label for training

[fierce pelican]

Track it separately.

[dim meteor]

i need the URL for that

[fierce pelican]

Your data doesn’t have a consistent shape

[dim meteor]

how exactly do i map the image to the URL

[fierce pelican]

You have a list that contains elements with two different shapes, does this make sense?

[img, label] is a list containing elements of two different shapes.

[dim meteor]

yes

but the label is required

and from the video which i am watching they did the exact same thing and got this instead:

<string>:6: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify ‘dtype=object’ when creating the ndarray

[fierce pelican]

That’s probably old then. ‘Deprecated’ means it’ll get removed in a future version

[dim meteor]

then how do i have the image and label together?

while still making it make sense

[fierce pelican]

I was just explaining the problem. Maybe start ‘over’ working from the end state. What are you trying to do?

Im not a CV guy, I was just answering the numpy part

[dim meteor]

make a dataset of images with the labels so i can train a TF model

[fierce pelican]

(And a fresh help thread with that question might help)

[dim meteor]

ok

@fierce pelican should i use a np array?

[fierce pelican]

My point was: your question is about training TF. Not about images and labels

Start with the end problem: ‘how do I train these images using xyz, etc’

[dim meteor]

im literally gonna just do list1+list2

and see if it works

because i cant find anything online

AND IT WORKED

we did all this discusion

completely ignoring that list1+list 2 works

[fierce pelican]

My first recommendation was not to use numpy operations, iirc. 🙂

(Or not to mix Python lists and Numpy like this)

[dim meteor]

i thought it woudlnt work becaause after combining i had to use numpy operators for splitting

but it still did

[dim meteor]

!close

[stable sand]

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