绘制频率直方图

!ls

Histogram and RoI.ipynb axon02.tif              test.jpg
Question 2.1 .ipynb     cell_nucleus.tif
axon01.tif              roi.tif

from PIL import Image
import numpy as np
from PIL import ImageOps
import matplotlib.pyplot as plt

# 打开图片并转换成灰度图
im = Image.open('axon01.tif').convert('L')

# 反转颜色
im = ImageOps.invert(im)

# display in macOS /Applications/Preview.app
# im.show()

# display in Jupyter Notebook
im

png

# 将灰度图片转换为 Numpy Array
im2array = np.array(im)

im2array.shape

(204, 1392)

# 将矩阵转化为向量
im2array = im2array.flatten()

# 204*1392 = 283968
len(im2array)

# 统计灰度值频率
freq = [0]*256
for i in range(len(im2array)):
    freq[im2array[i]] += 1

# 绘制灰度频率直方图
plt.figure(figsize=(25,10))
for i in range(0, 256):
    plt.bar(i, freq[i], color='r')
    plt.grid(color='gray', linewidth=0.1)

png

# 左上角坐标(0,0)，右下角下标(100,100)
# 裁剪出 100*100 的区域
box = (0, 0, 100, 100)
region = im.crop(box)

# 保存
region.save('roi.tif')

# 读取保存的 RoI
roi_im = Image.open('./roi.tif')

roi_im.size

(100, 100)

# 不转换为灰度图片
im = Image.open('axon01.tif')
im2array = np.array(im)
im2array = im2array.flatten()

# 统计像素值对应的像素个数
hist = [0] * (np.max(im2array)+1)
for i in range(0, len(im2array)):
    hist[im2array[i]] += 1

# 绘制直方图
plt.figure(figsize=(25,10))
for i in range(0, np.max(im2array)):
    plt.bar(i, hist[i], color='r')
    plt.grid(color='gray', linewidth=0.1)

png

使用 Pillow 库绘制直方图

# 求[0,255]像素频率
histogram = im.histogram()

# 这个分布符合直觉，大部分都是黑色
print(histogram)

[3341, 138883, 751, 581, 499, 536, 582, 11, 645, 687, 717, 774, 800, 895, 946, 1071, 1367, 6, 1131, 1178, 1212, 1256, 1384, 1407, 1491, 1548, 1649, 5, 1726, 1760, 1855, 1869, 1982, 2007, 1993, 2027, 2069, 3, 2161, 2230, 2316, 2194, 2337, 2293, 2304, 2316, 2427, 6, 2474, 2341, 2359, 2380, 2380, 2301, 3120, 2300, 2175, 1, 2208, 2151, 2059, 2089, 2068, 1994, 1891, 1957, 1775, 3, 1753, 1725, 1676, 1718, 1527, 1527, 1490, 1361, 1281, 4, 1718, 1254, 1101, 1092, 1027, 974, 894, 896, 796, 3, 820, 727, 720, 650, 670, 585, 548, 498, 487, 1, 442, 400, 387, 335, 339, 345, 293, 279, 220, 4, 235, 224, 227, 189, 196, 173, 165, 244, 147, 3, 118, 113, 109, 109, 109, 110, 98, 74, 76, 2, 75, 77, 74, 69, 73, 57, 75, 67, 56, 2, 57, 44, 63, 57, 47, 36, 38, 35, 40, 1, 43, 28, 41, 29, 34, 34, 26, 33, 21, 1, 35, 32, 8, 22, 38, 19, 34, 32, 33, 0, 20, 22, 10, 26, 16, 19, 11, 21, 12, 1, 23, 12, 29, 20, 10, 13, 7, 11, 19, 1, 18, 14, 6, 18, 13, 13, 9, 14, 10, 2, 10, 11, 13, 12, 10, 9, 11, 14, 4, 1, 15, 13, 12, 15, 10, 3, 11, 9, 9, 4, 14, 14, 15, 17, 16, 15, 19, 18, 16, 15, 19, 25, 34, 35, 32, 9, 45, 49, 54, 47, 65, 85, 101, 108, 92, 5, 102, 149, 141, 157, 185, 201, 207, 222, 275, 6, 318, 297]

# 最大值 138883 表示有 138883 个值为 1的像素
max(histogram)

for i, value in enumerate(im.histogram()):
    print(i, value)

# 像素总数 283968 = 204*1392
np.sum(histogram)

# 灰度级在 [0,255]
len(histogram)

plt.figure(figsize=(50,30))
for i in range(0, 256):
    plt.bar(i, histogram[i], color='r')
    plt.grid(color='gray', linewidth=0.1)

png

使用 Pillow 库绘制直方图#

使用 Pillow 库绘制直方图