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- OSError Traceback (most recent call last)
- <ipython-input-5-d55609bb9b39> in <module>()
- ----> 1 images, labels = dataset_preprocessing('/content/gdrive/My Drive/Data/cifar/train', '/content/gdrive/My Drive/Data/cifar/labels.txt', (32,32),'/content/gdrive/My Driv]/training_image_pickle')
- <ipython-input-4-79e4d13e78a2> in dataset_preprocessing(dataset_path, labels_file_path, image_size, image_paths_pickle)
- 14 image_paths = []
- 15
- ---> 16 for image_name in os.listdir(dataset_path):
- 17 try:
- 18 image_path = os.path.join(dataset_path, image_name)
- OSError: [Errno 5] Input/output error: '/content/gdrive/Data/cifar/train'
- def dataset_preprocessing(dataset_path, labels_file_path, image_size, image_paths_pickle):
- '''
- Load Images and labels from dataset folder.
- :param dataset_path:String, path to the train/test dataset folder
- :param image_size: Tuple, single image size
- :param image_path_pickle: String, name of a pickle file whre all imag paths will be saved
- '''
- with open(labels_file_path, 'r') as f:
- classes = f.read().split('n')[:-1]
- images = []
- labels = []
- image_paths = []
- for image_name in os.listdir(dataset_path):
- try:
- image_path = os.path.join(dataset_path, image_name)
- images.append(image_loader(image_path, image_size))
- image_paths.append(image_path)
- for idx in range(len(classes)):
- if classes[idx] in image_name: #Example: 0_frog.png
- labels.append(idx)
- except:
- pass
- with open(image_paths_pickle + '.pickle','wb') as f:
- pickle.dump(image_paths, f)
- assert len(images) == len(labels)
- return np.array(images), np.array(labels)
- from google.colab import drive
- drive.mount('/content/gdrive')
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