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示例通过共享内存读写图片
from multiprocessing import shared_memory
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
# 随机颜色 RGBA
def random_color()->tuple:
rgba = np.random.randint(0,255,size=4)
return tuple(rgba)
# 用随机数填充像素
def fill_random_pixels(img):
width, height = img.size
for x in range(width):
for y in range(height):
img.putpixel((x, y), random_color())
if __name__ == "__main__":
# 选择随机图片或者加载本地图片
random_image=False
img_width = 100
img_height = 100
img = Image.new('RGBA', (img_width, img_height))
if random_image:
fill_random_pixels(img)
origin_data = np.array(img)
else:
img_path = "C:\\Users\\mingxingwang\\Pictures\\qt-logo.png"
# 打开图片并转换为numpy数组
img = Image.open(img_path)
origin_data = np.array(img)
#------------- 数据写入共享内存
# 创建共享内存对象
shm_a = shared_memory.SharedMemory(create=True, name="my_share_mem",size=origin_data.nbytes)
#构造关联共享内存的数组
mem_array = np.ndarray(origin_data.shape, dtype=origin_data.dtype, buffer=shm_a.buf)
#copy 数据到共享内存
mem_array[:]=origin_data[:]
print(f"------------mem_array------------:\n{mem_array}\n")
#显示原始图片
origin_image = Image.frombytes(mode='RGBA',size=img.size,data=origin_data)
plt.imshow(origin_image)
plt.show()
#------------- 共享内存获取数据
existing_shm = shared_memory.SharedMemory(name='my_share_mem')
array_from_mem = np.ndarray(origin_data.shape, dtype=origin_data.dtype, buffer=existing_shm.buf)
print(f"------------array_from_mem------------:\n{array_from_mem}\n")
##从共享内存构造图片
img_from_mem = Image.frombytes(mode='RGBA',size=img.size,data=array_from_mem)
##显示从共享内存获取的图片
plt.imshow(img_from_mem)
plt.show()
shm_a.close()
shm_a.unlink()
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