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These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
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 that dataloader calls | |
def __getitem__(self, index): |
import numpy as np | |
import tensorflow as tf | |
from sklearn.datasets import make_blobs | |
# Set random seed (for reproducibility) | |
np.random.seed(1000) | |
# Create dataset | |
nb_samples=2000 |