- Create a virtual environment
conda create --name my_env_name python=3.8
or whatever Python version you may need.
- List available envs (2 different ways
conda env list
conda info --envs
- Activate virtual env
conda activate my_env_name
- Deactivate current environment
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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): |
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# Info on how to get your api key (kaggle.json) here: https://github.com/Kaggle/kaggle-api#api-credentials | |
!pip install kaggle | |
api_token = {"username":"USERNAME","key":"API_KEY"} | |
import json | |
import zipfile | |
import os | |
with open('/content/.kaggle/kaggle.json', 'w') as file: | |
json.dump(api_token, file) | |
!chmod 600 /content/.kaggle/kaggle.json | |
!kaggle config path -p /content |