mxnet record viewing.

ipcvl.py

import os, tarfile, subprocess
import mxnet as mx
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
from gluoncv import utils
from gluoncv.model_zoo import get_model
import matplotlib.pyplot as plt
import numpy as np

# gluoncv 같은게 없다고 할 수 도 있는데 그럼 그냥 위에서 빼셈 ㅋ 

data_iter = mx.io.ImageRecordIter(
    path_imglist=os.path.join(DATASET_PATH,'cropped_images','records','val1', 'kaggle-car-val1.lst'),
    path_imgrec=os.path.join(DATASET_PATH,'cropped_images','records','val1','kaggle-car-val1.rec'),
    path_imgidx=os.path.join(DATASET_PATH,'cropped_images','records','val1','kaggle-car-val1.idx'),
    data_shape=(3, 224, 224),label_width=1, # output data shape. An 227x227 region will be cropped from the original image.
    batch_size=4,rand_crop=True, # number of samples per batch
    resize=256, pad=1 # resize the shorter edge to 256 before cropping
    # ... you can add more augmentation options as defined in ImageRecordIter.
    )
    
    data_iter.reset()
batch = data_iter.next()
data = batch.data[0]
for i in range(4):
    plt.subplot(1,4,i+1)
    plt.imshow(data[i].asnumpy().astype(np.uint8).transpose((1,2,0)))
plt.show()