![]() ![]() abspath ( _file_ )) save_file = dataset_dir + "/mnist.pkl" train_num = 60000 test_num = 10000 img_dim = ( 1, 28, 28 ) img_size = 784 ( x_train, t_train ), ( x_test, t_test ) = load_mnist ( normalize = False, flatten = True ) # Show the sample image img = x_train label = t_train print ( label ) print ( img. reshape ( - 1, img_size ) print ( "Done" ) return data def _convert_numpy (): dataset = dataset_dir = os. About: OCR (Optical character recognition) is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo or from. open ( file_path, 'rb' ) as f : data = np. Click icon to show file QR code or save file to online storage services such as Google Drive or Dropbox. uint8, offset = 8 ) print ( "Done" ) return labels def _load_img ( file_name ): file_path = dataset_dir + "/" + file_name print ( "Converting " + file_name + " to NumPy Array. ![]() open ( file_path, 'rb' ) as f : labels = np. values (): _download ( v ) def _load_label ( file_name ): file_path = dataset_dir + "/" + file_name print ( "Converting " + file_name + " to NumPy Array. urlretrieve ( url_base + file_name, file_path ) print ( "Done" ) def download_mnist (): for v in key_file. exists ( file_path ): return print ( "Downloading " + file_name + ". Import urllib.request import gzip import pickle import os import numpy as np from PIL import Image def _download ( file_name ): file_path = dataset_dir + "/" + file_name if os. ![]()
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