import numpy as np
from PIL import Image
import PIL .Image as pImg
im = pImg.open(r"F:\artificial_inligence\DL\liev_CD\project2\yolo2-pytorch-master\demo\horses.jpg")
h,w=im.size
c=len(im.mode)
scale = np.random.uniform() / 10. + 1.
max_offx = (scale - 1.) * w
max_offy = (scale - 1.) * h
print("w,max_offx:\n",w,max_offx)
print("h,max_offy:\n",h,max_offy)
offx = int(np.random.uniform() * max_offx)
offy = int(np.random.uniform() * max_offy)
im = im.resize((int(w/scale),int(h/scale)))
print("1.im:\n",im)
im=np.array(im)
print("offy,offx:\n",offy,offx)
im = im[offy: (offy + h), offx: (offx + w)]
im = Image.fromarray(im)
print("2.im:\n",im)
flip = np.random.uniform() > 0.5
if flip:
im = im.rotate(180)
im.show()