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Django Ajax Image/file Upload

` Upload image directly to server without any page reload with ajax.

Here is a nutshell of uploading image in django with ajax `

models

Guide on ubuntu to get better user experience !

We assume you have installed ubuntu 16 or newer version. to get better option, please install ubutn as lagacy mode: here you go for ths tutorial Install Ubuntu in lagacy mode

During installation, make sure you have customized your partision in better way. check the following checklist during partition.

You have give size to SWAP as much campacity as your RAM has
Give HOME size highest

Guide on how to create and set up a Dockerized web app using Django REST APIs and ReactJS

Hopefully this will answer "How do I setup or start a Django project using REST Framework and ReactJS?"

This is a guide to show you step by step how this can be setup. If you just want to get started, use the cookiecuter I set up cookiecutter-django-reactjs. It basically is a fork of pydanny's cookiecutter, just added the front-end stuff :).

I created this because it was SUCH a pain in the ass setting up a project using all the latest technologies. After some research, I figured it out and have it working. The repo that implements this is located here. Feel free to use it as a boilerplate ;)

Main features:

Django REST APIs

	if DEBUG:
	EMAIL_HOST = 'localhost'
	EMAIL_PORT = 1025
	EMAIL_HOST_USER = ''
	EMAIL_HOST_PASSWORD = ''
	EMAIL_USE_TLS = False
	DEFAULT_FROM_EMAIL = 'testing@example.com'

	version: '2.0'

	services:
	postgres:
	image: postgres
	container_name: mamun-db
	working_dir: /usr/src/app
	volumes:
	- ./data:/usr/src/app
	environment:

	#facebook marketplace
	from selenium import webdriver
	from time import sleep
	from selenium.webdriver.common.keys import Keys
	from selenium.webdriver.support.ui import WebDriverWait
	from selenium.webdriver.common.by import By
	from selenium.webdriver.support import expected_conditions as EC
	from pymongo import MongoClient

	class App:

	from nltk.corpus import wordnet
	from nltk.tokenize import word_tokenize
	from random import randint
	import nltk.data

	# Load a text file if required
	text = "Pete ate a large cake. Sam has a big mouth."
	output = ""

	# Load the pretrained neural net

	import cv2
	import numpy as np
	import urllib.request
	import time

	start_time = time.time()
	for i in range(1, 51):
	try:
	req = urllib.request.Request(
	'https://assets.pokemon.com/assets/cms2/img/pokedex/detail/' + '{:03d}'.format(i) + '.png')

	import os
	import argparse
	from PIL import Image

	DEFAULT_SIZE = (320, 180)


	def resize_image(input_dir, infile, output_dir="resized", size=DEFAULT_SIZE):
	outfile = os.path.splitext(infile)[0] + "_resized"
	extension = os.path.splitext(infile)[1]