Python中的分類圖像

Question

我想將.jpg轉換爲分類數組。對於圖像中的每個像素，我都有RGB值，並且我想將這些值與唯一值相關聯（請參閱圖像）。你有什麼想法做到這一點？我在scikit圖像和其他圖像處理模塊中做了一些研究，但沒有成功。

jpg to categorical

Answer 1

第一部分溶液在https://stackoverflow.com/a/30524039/3104727找到）。在此再現的，以便與此image

from PIL import Image 
import operator 
from collections import defaultdict 
import numpy as np 

input_path = 'TI_test.jpg' 
output_path = 'TI_output.png' 
size = (200,200) 

# Then we declare the palette - this should contain all colours. 
palette = [(112, 137, 98), #green 
      (96, 97, 115), #blue 
      (140, 129, 49), #gold 
      (184, 31, 36), #red 
      ] 
while len(palette) < 256: 
    palette.append((0, 0, 0)) 

# The code below will declare palette for PIL, since PIL needs flat 
# array rather than array of tuples: 
flat_palette = reduce(lambda a, b: a+b, palette) 
assert len(flat_palette) == 768 

# Now we can declare an image that will hold the palette. We'll use 
# it to reduce the colours from the original image later. 
palette_img = Image.new('P', (1, 1), 0) 
palette_img.putpalette(flat_palette) 

# Here we open the image and quantize it. We scale it to size eight 
# times bigger than needed, since we're going to sample the average 
# output later. 
multiplier = 8 
img = Image.open(input_path) 
img = img.resize((size[0] * multiplier, size[1] * multiplier),Image.BICUBIC) 
img = img.quantize(palette=palette_img) #reduce the palette 

# We need to convert it back to RGB so that we can sample pixels now: 
img = img.convert('RGB') 

# Now we're going to construct our final image. To do this, we'll 
# sample how many pixels of each palette color each square in the 
# bigger image contains. Then we'll choose the color that occurs most 
# often. 

out = Image.new('RGB', size) 
for x in range(size[0]): 
    for y in range(size[1]): 
     #sample at get average color in the corresponding square 
     histogram = defaultdict(int) 
     for x2 in range(x * multiplier, (x + 1) * multiplier): 
      for y2 in range(y * multiplier, (y + 1) * multiplier): 
       histogram[img.getpixel((x2,y2))] += 1 
     color = max(histogram.iteritems(),key=operator.itemgetter(1))[0] 
     out.putpixel((x, y), color) 

下面的代碼的工作它被添加到變換的RGB圖像中灰度級，然後在分類值的陣列（0到n的顏色）。獨特灰度的

out2 = out.convert('L') 

值列表

color = list(set(list(out2.getdata()))) 

準分類值（0到n種顏色）到每個像素

for x in range(size[0]): 
    for y in range(size[1]): 
     if out2.getpixel((x,y)) == color[0]: 
      out2.putpixel((x,y),0) 
     elif out2.getpixel((x,y)) == color[1]: 
      out2.putpixel((x,y),1) 
     elif out2.getpixel((x,y)) == color[2]: 
      out2.putpixel((x,y),2) 
     else: 
      out2.putpixel((x,y),3) 

圖像變換到numpy的陣列

pix = np.array(out2)