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---
license: mit
language:
- ko
tags:
- asian
- face
- faces
---
Download LINK
https://drive.google.com/drive/folders/1IpR5mRFVFwPfWtcy-HO8Xj2M-TCZKxKK?usp=sharing
```
!pip list
!pip install matplotlib
!pip install --no-build-isolation scikit-learn
!pip install numpy scipy cython
!pip install mxnet
!pip install opencv-python
!pip install numpy==1.23.5
!pip install mxnet
import mxnet as mx
from mxnet import recordio
import matplotlib.pyplot as plt
import cv2
import os
path_imgidx = 'train.idx' # path to train.rec
path_imgrec = 'train.rec' # path to train.idx
imgrec = recordio.MXIndexedRecordIO(path_imgidx, path_imgrec, 'r')
i = 0
while True:
try:
print(i)
header, s = recordio.unpack(imgrec.read_idx(i+1))
#print(str(header.label))
#img = np.array(mx.image.imdecode(s))
img = mx.image.imdecode(s).asnumpy()
#print(type(img))
path = os.path.join('images',str(header.label))
if not os.path.exists(path):
os.makedirs(path)
path = os.path.join(path,str(i))
#fig = plt.figure(frameon=False)
#fig.set_size_inches(124,124)
#ax = plt.Axes(fig, [0., 0., 1., 1.])
#ax.set_axis_off()
#fig.add_axes(ax)
#ax.imshow(img, aspect='auto')
#dpi=1
#fname= str(i)+'jpg'
#fig.savefig(fname, dpi)
#plt.savefig(path+'.jpg',bbox_inches='tight',pad_inches=0)
(b,g,r)=cv2.split(img)
img = cv2.merge([r,g,b])
#w,h = img.size
#print((img.shape))
cv2.imwrite(path+'.jpg',img)
i += 1
except EOFError:
break
# 1~ 2369931.jpg 17gb
``` |