# Image from numpy array appears colorless

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colorlessarrayimagenumpy
90%

Be careful if the mask image is a grayscale image and a 2D (no color dimension) ndarray, If multiplication is performed as it is, an error occurs

Example_snippet/controller/utility/_colorless.js/ dst = cv2.addWeighted(src1, al. . .
`dst = cv2.addWeighted(src1, alpha, src2, beta, gamma[, dst[, dtype]])`
88%

Converting the loaded images to the NumPy array and back,Convert to NumPy Array and Back,print(data) gives the value of each pixel of the NumPy array image, ,Reading images as arrays in Keras API and OpenCV

Example_snippet/controller/utility/_colorless.js/ 1pip install Pillow. . .
`1 pip install Pillow`
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Importing image data into Numpy arrays,So, you have your data in a numpy array (either by importing it, or by generating it), Let's render it

Example_snippet/controller/utility/_colorless.js/ In [1]: %matplotlib inline . . .
`In[1]: % matplotlib inline`
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To apply PCA on image data, the images need to be converted to a one-dimensional vector representation using, for example, NumPy’s flatten() method,,These derivative filters are easy to implement using the standard convolution available in the scipy

Example_snippet/controller/utility/_colorless.js/ from PIL import Image pil_im . . .
```from PIL
import Image

pil_im = Image.open('empire.jpg')```
Step 2 continued with pil_im = Image.open('empire.jp. . .
`pil_im = Image.open('empire.jpg').convert('L')`
Step 3 continued with from PIL import Image import o. . .
```from PIL
import Image
import os

for infile in filelist:
outfile = os.path.splitext(infile)[0] + ".jpg"
if infile != outfile:
try:
Image.open(infile).save(outfile)
except IOError:
print "cannot convert", infile```
Step 4 continued with import os def get_imlist(path. . .
```import os

def get_imlist(path):
""
"  Returns a list of filenames for
all jpg images in a directory.
""
"

return [os.path.join(path, f) for f in os.listdir(path) if f.endswith('.jpg')]```
Step 5 continued with pil_im.thumbnail((128,128)). . .
`pil_im.thumbnail((128, 128))`
Step 6 continued with box = (100,100,400,400) region. . .
```box = (100, 100, 400, 400)
region = pil_im.crop(box)```
Step 7 continued with region = region.transpose(Imag. . .
```region = region.transpose(Image.ROTATE_180)
pil_im.paste(region, box)```
Step 8 continued with out = pil_im.resize((128,128)). . .
`out = pil_im.resize((128, 128))`
Step 9 continued with out = pil_im.rotate(45). . .
`out = pil_im.rotate(45)`
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I need to know if it's possible to grab an images RGB values from it's (get)data if it's colorless, I currently have a piece of code that looks like this (np=numpy):,You do this before converting to a numpy array

Example_snippet/controller/utility/_colorless.js/ Image image = Image.open(path). . .
```Image image = Image.open(path)
n, m = image.size
data = np.array(image.getdata())
R = np.zeros(n * m, dtype = np.float)
G = np.zeros(n * m, dtype = np.float)
B = np.zeros(n * m, dtype = np.float)

for x in range(0, n * m):
RGB = data[x]
R[x] = RGB[0]
G[x] = RGB[1]
B[x] = RGB[2]```
Step 2 continued with indexError: invalid index to s. . .
`indexError: invalid index to scalar variable`
Step 3 continued with R[x] = RGB[0] . . .
`R[x] = RGB[0]`
40%

Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers ,I would like to create following 2x2 image from numpy array using OpenCV,,Stack Overflow en español, Meta Stack Overflow

Example_snippet/controller/utility/_colorless.js/ import cv2 import numpy as np . . .
```import cv2
import numpy as np

blue = (255, 0, 0)
green = (0, 255, 0)
red = (0, 0, 255)

image = np.array([
[blue, green],
[red, blue]
], dtype = np.uint8)

image = cv2.resize(image, (200, 200), interpolation = cv2.INTER_AREA)

cv2.imwrite('2x2.jpg', image)```