Pytorch DataLoader for custom dataset to load data image and mask correctly with a window size Question: I am trying to write a custom data loader for a dataset where the directory structures is as follows: All_data | ->Numpy_dat | | | -> dat_0 | -> dat_{0}_{0}.npy | . | . | -> dat_1 | …
Pytorch DataLoader for custom dataset Question: I am trying to write a custom data loader for a dataset where the directory structures is as follows: All_data | ->Numpy_dat | | | -> dat_0 | -> dat_{0}_{0}.npy | . | . | -> dat_1 | -> dat_{0}_{0}.npy | -> dat_{0}_{1}.npy | . | . |->mask_numpy | …
Pytorch DataLoader changes dict return values Question: Given a Pytorch dataset that reads a JSON file as such: import csv from torch.utils.data import IterableDataset from torch.utils.data import DataLoader2, DataLoader class MyDataset(IterableDataset): def __init__(self, jsonfilename): self.filename = jsonfilename def __iter__(self): with open(self.filename) as fin: reader = csv.reader(fin) headers = next(reader) for line in reader: yield dict(zip(headers, …
Turning variable into a torch Tensor. Afterwards tensor is empty / has no element Question: The following is my Code. The "sequences" are my training data in the form [139 rows x 4 columns], 0) where the 139×4 are my signals and the 0 is my encoded label. def __getitem__(self, idx): sequence, label = self.sequences[idx] …
creating a train and a test dataloader Question: I have actually a directory RealPhotos containing 17000 jpg photos. I would be interested in creating a train dataloader and a test dataloader ls RealPhotos/ 2007_000027.jpg 2008_007119.jpg 2010_001501.jpg 2011_002987.jpg 2007_000032.jpg 2008_007120.jpg 2010_001502.jpg 2011_002988.jpg 2007_000033.jpg 2008_007123.jpg 2010_001503.jpg 2011_002992.jpg 2007_000039.jpg 2008_007124.jpg 2010_001505.jpg 2011_002993.jpg 2007_000042.jpg 2008_007129.jpg 2010_001511.jpg 2011_002994.jpg 2007_000061.jpg 2008_007130.jpg …
What does next() and iter() do in PyTorch's DataLoader() Question: I have the following code: import torch import numpy as np import pandas as pd from torch.utils.data import TensorDataset, DataLoader # Load dataset df = pd.read_csv(r’../iris.csv’) # Extract features and target data = df.drop(‘target’,axis=1).values labels = df[‘target’].values # Create tensor dataset iris = TensorDataset(torch.FloatTensor(data),torch.LongTensor(labels)) # …
KeyError when enumerating over dataloader Question: I’m trying to iterate over a pytorch dataloader initialized as follows: trainDL = torch.utils.data.DataLoader(X_train,batch_size=BATCH_SIZE, shuffle=True, **kwargs) where X_train is a pandas dataframe like this one: So, I’m not being able to do the following statement, since I’m getting a KeyError in the ‘enumerate’: for batch_idx, (data, _) in enumerate(trainDL): …
How to make the trainloader use a specific amount of images? Question: Assume I am using the following calls: trainset = torchvision.datasets.ImageFolder(root="imgs/", transform=transform) trainloader = torch.utils.data.DataLoader(trainset,batch_size=4,shuffle=True,num_workers=1) As far as I can tell, this defines the trainset as consisting of all the images in the folder "images", with labels as defined by the specific folder location. …
