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loader.py
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loader.py
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import glob
import numpy as np
from PIL import Image
from matplotlib import pyplot as plt
from scipy.stats import entropy as scipy_entropy
class Loader:
def __init__(self, natural_images_dir,
artificial_images_dir):
self.natural_images = glob.glob(natural_images_dir + "/*.pgm", recursive=True)
self.artificial_images = glob.glob(artificial_images_dir + "/*.pgm", recursive=True)
def generateHistograms(self):
for path in self.natural_images:
self.generateHistogram(path)
for path in self.artificial_images:
self.generateHistogram(path)
def generateHistogram(self, path):
image = Image.open(path)
histr = image.histogram()
histr_file_name = path.replace(".pgm", "_hist.png")
plt.figure()
plt.plot(histr)
plt.xlim([0, 256])
plt.savefig(histr_file_name)
plt.close()
def getNaturalImages(self):
images = []
for path in self.natural_images:
image = np.asarray(Image.open(path))
images.append(image)
return images
def getNaturalImagesAsNumpyArray(self):
images = []
for path in self.natural_images:
image = Image.open(path)
images.append((image, path))
return images
def getArtificialImages(self):
images = []
for path in self.artificial_images:
image = np.asarray(Image.open(path))
images.append(image)
return images
def getArtificialImagesAsNumpyArray(self):
images = []
for path in self.artificial_images:
image = Image.open(path)
images.append((image, path))
return images
def imageToBits(self, image):
image = np.asarray(image, dtype=np.uint8)
image = np.unpackbits(image)
return image
def entropy(self, img, base=2): # 2 stands for Shannon entropy
_, counts = np.unique(img, return_counts=True)
return scipy_entropy(counts, base=base)
if __name__ == "__main__":
loader = Loader(natural_images_dir="data/obrazy",
artificial_images_dir="data/rozklady")
loader.generateHistograms()
for img in loader.getArtificialImages():
print(loader.entropy(img))