danallison

from sshtunnel import SSHTunnelForwarder
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from functools import wraps

# secrets.py contains credentials, etc.
import secrets

def get_engine_for_port(port):
    return create_engine('postgresql://{user}:{password}@{host}:{port}/{db}'.format(

epignatelli

"""
An implementation of the pytorch Subset that returns an instance of the original dataset with a reduced number of items.
This has two benefits:
  - It allows to stil access the attributes of the Dataset class, such as methods, or properties.
  - You can use the usual python index notation with slices to chunk the dataset, rather than creating a list of indices

"""
class Dataset(object):
  def __init__(self, iterable):
    self.items = iterable

mlaves

jph00

# I added all the imports by hand
import torch
from torchvision.datasets import ImageFolder
from torchvision import transforms,models
from torch import nn,optim

# For all functions including this one, I wrote the name and docstring, and sometimes also the param names
def finetune(folder, model):
    """fine tune pytorch model using images from folder and report results on validation set"""
    if not os.path.exists(folder): raise ValueError(f"{folder} does not exist")

minesh1291

import json
import numpy as np
from pycocotools import mask
from skimage import measure

ground_truth_binary_mask = np.array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                                     [  0,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                                     [  0,   0,   0,   0,   0,   1,   1,   1,   0,   0],
                                     [  0,   0,   0,   0,   0,   1,   1,   1,   0,   0],
                                     [  0,   0,   0,   0,   0,   1,   1,   1,   0,   0],

minesh1291

#!/bin/bash

# Check if the script is run with root privileges
if [ "$EUID" -ne 0 ]; then
  echo "Please run as root"
  exit
fi

# Determine the log file based on the distribution
if [ -f /var/log/auth.log ]; then