05-图像处理

# https://blog.csdn.net/qq_33883462/article/details/81050795
from PIL import Image
import numpy as np 
import matplotlib.pyplot as plt 
import cv2
from io import StringIO
import PIL.Image as pimg
def fig2data (fig):
    """
    把 plt.figure 保存为 numpy 文件。
    @brief Convert a Matplotlib figure to a 4D numpy array with RGBA channels and return it
    @param fig a matplotlib figure
    @return a numpy 3D array of RGBA values
    """
    # draw the renderer
    fig.canvas.draw ( )
    # Get the RGBA buffer from the figure
    w,h = fig.canvas.get_width_height()
    buf = np.fromstring ( fig.canvas.tostring_argb(), dtype=np.uint8 )
    buf.shape = ( w, h,4 )
    # canvas.tostring_argb give pixmap in ARGB mode. Roll the ALPHA channel to have it in RGBA mode
    buf = np.roll ( buf, 3, axis = 2 )
    return buf
def fig2img(fig):
    """
    把 plt.figure 保存为 PIL.Image 文件
    @brief Convert a Matplotlib figure to a PIL Image in RGBA format and return it
    @param fig a matplotlib figure
    @return a Python Imaging Library ( PIL ) image
    """
    # put the figure pixmap into a numpy array
    buf = fig2data (fig)
#     print("buf")
#     print(type(buf))
#     print(buf.shape)
    w, h, d = buf.shape
    return Image.frombytes("RGBA", (w,h), buf.tostring())
# fig = plt.figure(figsize=(2,2), dpi=128)
fig = plt.figure(figsize=(4,4), dpi=64)
npy_path = '/data1/huangyongye/github/sbir/data/sketchy_coord_original/airplane/n02691156_10151-1.npy'
coord = np.load(npy_path)
# 根据最后的一位划分笔画
cut_ids = filter(lambda i: coord[:, -1][i] == 1, range(len(coord)))
left = 0
right = 0
count = 0
for right in cut_ids:
    x = coord[left:right+1, 0]
    y = 800 - coord[left:right+1, 1]
    plt.plot(x, y, 'k-', label=str(count))
    plt.axis("off")
    left = right + 1
    count += 1
# 把 plt 的输出结果转为 numpy 格式
img_arr = fig2data(fig)
print(img_arr.shape)
# 把 plt 的输出结果转为 PIL.Image 格式
img = fig2img(fig)
print(type(img))
img