Madhu Bagroy Madhu612

Madhu612 / classifier_from_little_data_script_2.py

Created October 15, 2018 00:33 — forked from fchollet/classifier_from_little_data_script_2.py

Updated to the Keras 2.0 API.

	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.
	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data
	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	- created cats/ and dogs/ subfolders inside train/ and validation/
	- put the cat pictures index 0-999 in data/train/cats

Madhu612 / data_loader.py

Created July 16, 2018 21:16 — forked from kevinzakka/data_loader.py

Train, Validation and Test Split for torchvision Datasets

	"""
	Create train, valid, test iterators for CIFAR-10 [1].
	Easily extended to MNIST, CIFAR-100 and Imagenet.

	[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
	"""

	import torch
	import numpy as np

Madhu612 / pytorch_image_folder_with_file_paths.py

Created July 16, 2018 21:02 — forked from andrewjong/pytorch_image_folder_with_file_paths.py

PyTorch Image File Paths With Dataset Dataloader

	import torch
	from torchvision import datasets

	class ImageFolderWithPaths(datasets.ImageFolder):
	"""Custom dataset that includes image file paths. Extends
	torchvision.datasets.ImageFolder
	"""

	# override the __getitem__ method. this is the method dataloader calls
	def __getitem__(self, index):