Ehsan Yaghoubi Ehsan-Yaghoubi

## install virtualenv ubuntu 16.04.md

      
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                Ehsan-Yaghoubi
                / install virtualenv ubuntu 16.04.md
            
            
              Created
              December 9, 2019 15:52
                — forked from frfahim/install virtualenv ubuntu 16.04.md
            
              
                How to install virtual environment on ubuntu 16.04
              
          
    How to install virtualenv:

Install pip first

sudo apt-get install python3-pip

Then install virtualenv using pip3

sudo pip3 install virtualenv 


## instructions.txt
With normal user:

If repository is empty.

$ mkdir REPO
$ cd REPO
$ touch README.md
$ git init
$ git add README.md
$ git commit -m "Message to be public displayed"

## tensorflow_finetune.py
"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz

## pytorch_finetune.py
import argparse
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data import DataLoader

import torchvision
import torchvision.transforms as T
from torchvision.datasets import ImageFolder
	With normal user:

	If repository is empty.

	$ mkdir REPO
	$ cd REPO
	$ touch README.md
	$ git init
	$ git add README.md
	$ git commit -m "Message to be public displayed"
	"""
	Example TensorFlow script for finetuning a VGG model on your own data.
	Uses tf.contrib.data module which is in release v1.2
	Based on PyTorch example from Justin Johnson
	(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)

	Required packages: tensorflow (v1.2)
	Download the weights trained on ImageNet for VGG:
	```
	wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz
	import argparse
	import torch
	import torch.nn as nn
	from torch.autograd import Variable
	from torch.utils.data import DataLoader

	import torchvision
	import torchvision.transforms as T
	from torchvision.datasets import ImageFolder