add .rec conversion cod and image data processing code

+import numpy as np
+import os
+
+np.random.seed(3)
+
+from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
+# 원본 위
+optInputPath = '~/yoga/'
+# 저장될 위치
+optOutputPath = '~/preview/'
+
+# 이미지 크기 조정 비율
+optRescale = 1./255
+# 이미지 회전
+optRotationRange=10
+# 이미지 수평 이동
+optWidthShiftRange=0.2
+# 이미지 수직 이동
+optHeightShiftRange=0.2
+# 이미지 밀림 강도 
+optShearRange=0.5
+# 이미지 확대/ 축소 
+optZoomRange=[0.9,2.2]
+# 이미지 수평 뒤집기 
+optHorizontalFlip = True
+# 이미지 수직 뒤집기 
+optVerticalFlip = False
+optFillMode='nearest'
+# 이미지당 늘리는 갯수 
+optNbrOfIncreasePerPic = 3
+# 배치 수 
+optNbrOfBatchPerPic = 2
+
+train_datagen = ImageDataGenerator(rescale=optRescale, 
+                                   rotation_range=optRotationRange,
+                                   width_shift_range=optWidthShiftRange,
+                                   height_shift_range=optHeightShiftRange,
+                                   shear_range=optShearRange,
+                                   zoom_range=optZoomRange,
+                                   horizontal_flip=optHorizontalFlip,
+                                   vertical_flip=optVerticalFlip,
+                                   fill_mode=optFillMode)
+
+def checkFoler(path):
+    try:
+        if not(os.path.isdir(path)):
+            os.makedirs(os.path.join(path))
+    except OSError as e:
+        if e.errno != errno.EEXIST:                        
+            raise            
+
+def increaseImage(path ,folder):
+    for index in range(0,optNbrOfIncreasePerPic):                                   
+        img = load_img(path)
+        x = img_to_array(img)
+        x = x.reshape((1,) + x.shape)
+        i = 0
+        checkFoler(optOutputPath+folder)               
+        print('index : ' + str(index))
+        for batch in train_datagen.flow(x, batch_size=1, save_to_dir=optOutputPath+folder, save_prefix='tri', save_format='jpg'):
+            i += 1
+            print(folder + " " + str(i))
+            if i >= optNbrOfBatchPerPic: 
+                break
+
+def generator(dirName):
+    checkFoler(optOutputPath)
+    try:
+        fileNames = os.listdir(dirName)
+        for fileName in fileNames:
+            fullFileName = os.path.join(dirName, fileName)
+            if os.path.isdir(fullFileName):                
+                generator(fullFileName)
+            else:
+                ext = os.path.splitext(fullFileName)[-1]
+                folderName = os.path.splitext(fullFileName)[0].split('/')[-2]
+                if(ext == '.jpg'):                    
+                    increaseImage(fullFileName, folderName)               
+                    
+    except PermissionError:
+        pass
+
+if __name__ == "__main__":
+        generator(optInputPath) 

+import mxnet as mx
+import os
+
+MXNET_HOME="/home/eraser/mxnet"
+
+os.system('python3 %s/tools/im2rec.py /home/eraser/train /home/eraser/yoga_data/train --recursive --list --num-thread 8'%MXNET_HOME)
+os.system('python3 %s/tools/im2rec.py /home/eraser/validation /home/eraser/yoga_data/validation --recursive --list --num-thread 8'%MXNET_HOME)
+
+os.system('python3 %s/tools/im2rec.py /home/eraser/train /home/eraser/yoga_data/train --recursive --pass-through --pack-label --num-thread 8'%MXNET_HOME)
+os.system('python3 %s/tools/im2rec.py /home/eraser/validation /home/eraser/yoga_data/validation --recursive --pass-through --pack-label --num-thread 8'%MXNET_HOME)
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