CODEWITHSUNDEEP
deep-learningpytorchgoogle-colaboratory
Shafaq
Shafaq

Reputation: 11

how to upload and read a zip file containing training and testing images data from google colab from my pc

I am new to google colab. I am implementing a pretrained vgg16 and resnet50 model using pytorch, but I am unable to load my file and read it as it returns an error of no directory found

I have uploaded the data through file also I have used to upload it using 

from google.colab import files
uploaded = files.upload()

The file got uploaded but when I tried to unzip it because it is a zip file using !unzip content/cropped_months then it says

no file found 

import torch
import torch.nn as nn
import torch.optim as optim
from torchvision.transforms import *
from torch.optim import lr_scheduler
from torch.autograd import Variable
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import os
import copy

from google.colab import files
uploaded = files.upload()

!unzip content/cropped_months 

data_dir = 'content/cropped_months'
​
#Define transforms for the training data and testing data
train_transforms = transforms.Compose([transforms.RandomRotation(30),transforms.RandomResizedCrop(224),transforms.RandomHorizontalFlip(),transforms.ToTensor(),transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])
​
test_transforms = transforms.Compose([transforms.Resize(256),transforms.CenterCrop(224),transforms.ToTensor(),transforms.Normalize([0.485, 0.456, 0.406],[0.229, 0.224, 0.225])])
​
#pass transform here-in
train_data = datasets.ImageFolder(data_dir + '/train', transform=train_transforms)
test_data = datasets.ImageFolder(data_dir + '/test', transform=test_transforms)
​
#data loaders
trainloader = torch.utils.data.DataLoader(train_data, batch_size=8, shuffle=True)
testloader = torch.utils.data.DataLoader(test_data, batch_size=8, shuffle=True)
​
print("Classes: ")
class_names = train_data.classes
print(class_names)

first error

unzip: cannot find or open content/cropped_months, content/cropped_months.zip or content/cropped_months.ZIP.

second error

--------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) in () 16 17 #pass transform here-in ---> 18 train_data = datasets.ImageFolder(data_dir + '/train', transform=train_transforms) 19 test_data = datasets.ImageFolder(data_dir + '/test', transform=test_transforms) 20

2 frames /usr/local/lib/python3.6/dist-packages/torchvision/datasets/folder.py in _find_classes(self, dir) 114 if sys.version_info >= (3, 5): 115 # Faster and available in Python 3.5 and above --> 116 classes = [d.name for d in os.scandir(dir) if d.is_dir()] 117 else: 118 classes = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir, d))]

FileNotFoundError: [Errno 2] No such file or directory: 'content/cropped_months (1)/train'

Upvotes: 1

Views: 5359

Answers (2)

ahmed barbouche
ahmed barbouche

Reputation: 61

I think you can use PySurvival library is compatible with Torch , here the link :

https://square.github.io/pysurvival/miscellaneous/save_load.html

Upvotes: 0

Fábio Perez
Fábio Perez

Reputation: 26048

You are probably trying to access the wrong path. In my notebook, the file was uploaded to the working directory.

Use google.colab.files to upload the zip.

from google.colab import files
files.upload()

Upload your file. Google Colab will display where it was saved:

Saving dummy.zip to dummy.zip

Then just run !unzip:

!unzip dummy.zip

Upvotes: 1

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