CODEWITHSUNDEEP
pythonpython-3.xmachine-learningscikit-learnpython-imaging-library
Medo
Medo

Reputation: 1032

Is it possible to convert 3D image to one vector?

In this code (courtesy to this answer):

from PIL import Image
import numpy as np


def load_image(infilename):
    img = Image.open(infilename)
    img.load()
    data = np.asarray(img, dtype="int32")
    return data


def save_image(npdata, outfilename):
    img = Image.fromarray(np.asarray(np.clip(npdata, 0, 255), dtype="uint8"), "L")
    img.save(outfilename)

data = load_image('cat.0.jpg')
print(data.shape)

The value of print(data.shape) is a tuple of three dim (374, 500, 3). Thus, I have these questions:

  1. What does this tuple represent?
  2. To be used for machine learning classification purpose, does it make sense to convert such a tuple data into one dimension vector? If so, how?

Thank you very much.

Upvotes: 0

Views: 572

Answers (2)

Jonathan R
Jonathan R

Reputation: 3928

The dimensions are: (row,col,channel) Yes it often makes sense to feed a 1D array into a Neural Net, for example if you use a fully connected network. To reshape you have multiple options:

  1. Use the reshape function

    data.reshape(-1)

  2. Use the flatten function

    data.flatten()

Upvotes: 1

itdoesntwork
itdoesntwork

Reputation: 4802

  1. 374 rows of 500 columns of RGB (3) values (or pixels), or some permutation of these dimensions.

  2. Maybe. Though remember that any 1D encoding of this discards two-dimensional distance information between different pixels. If you're working with neural networks, look into convolutional neural networks to see how they deal with this problem.

Upvotes: 0

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