- Our main goal is to use django to create a project.
- Since, django is a python framework, we need to install python to run it.
- However, there are 2 major versions of python available - python 2 and python 3.
- We're going to use python 3 since it's the latest version available and is way better than python 2.
- Pip is the package manager for python, we use pip to install python programs so we don't have to download, configure and install it ourselves.
- Managing python versions (2 and 3) is a bit tedious, so we're going to use virtualenv.
- Virtualenv will help us create isolated environment for our django project so we can set which python version we're going to use and not worry about anything at all. There are many other benefits of using it which you'll see later.
#include <stdio.h> | |
// 1 2 3 4 5 | |
// 1 3 4 5 -1 | |
void deleteItem (int list[], int z, int index) { | |
int i = index; | |
while (i < z) { | |
if ((i + 1) < z) // if there's an item on the left | |
list[i] = list[i + 1]; | |
else |
#include <stdio.h> | |
#define W 3 | |
#define H 2 | |
void inputMatrix (int matrix[H][W]) { | |
int i, j; | |
for (i = 0; i < H; i++) { | |
for (j = 0; j < W; j++) { | |
scanf("%d", &matrix[i][j]); | |
} |
// Copyright BDH Lab 2018 | |
#include <iostream> | |
#include <string> | |
using std::cout; | |
using std::string; | |
// IO class | |
class IO { | |
string output; |
2018-12-26T17:30:20.557758+00:00 app[web.1]: [2018-12-26 17:30:20 +0000] [10] [INFO] Worker exiting (pid: 10) | |
2018-12-26T17:30:20.860732+00:00 app[web.1]: [2018-12-26 17:30:20 +0000] [4] [INFO] Shutting down: Master | |
2018-12-26T17:30:20.861125+00:00 app[web.1]: [2018-12-26 17:30:20 +0000] [4] [INFO] Reason: Worker failed to boot. | |
2018-12-26T17:30:21.089174+00:00 heroku[web.1]: State changed from up to crashed | |
2018-12-26T17:30:21.069711+00:00 heroku[web.1]: Process exited with status 3 | |
2018-12-26T17:30:21.000000+00:00 app[api]: Build succeeded | |
2018-12-26T17:30:35.331409+00:00 heroku[router]: at=error code=H10 desc="App crashed" method=GET path="/" host=cirrhus.herokuapp.com request_id=962f35a8-2378-419b-bbb4-cd8f6b6219e5 fwd="103.195.204.5" dyno= connect= service= status=503 bytes= protocol=https | |
2018-12-26T17:30:36.799912+00:00 heroku[router]: at=error code=H10 desc="App crashed" method=GET path="/apple-touch-icon-precomposed.png" host=cirrhus.herokuapp.com request_id=e4fde1f8-856a-41c3-96a2-c12bd405681c fwd=" |
[18:27] <trumanshow19> Would someone mind help iron out the | |
inconsistencies in my head with respect to purity in | |
Haskell. Statement 1: Haskell is a purely functional lanugage, S2: | |
Haskell is not impure, but... S3: f :: a -> a is a "pure" function as | |
opposed to a -> IO a. | |
[18:27] <trumanshow19> If a -> is pure, to distinguish a -> IO a, then | |
how do I describe the latter, is there is no impurity in Haskell ? | |
[18:28] <trumanshow19> The only opposite of pure I know is impure. |
import cv2 | |
import imutils | |
import numpy as np | |
import pytesseract | |
from PIL import Image | |
def wait(): | |
cv2.waitKey(0) | |
cv2.destroyAllWindows() |
If anyone is up for creating a car number plate detector based on machine learning (such as neural networks), tons of images for training is required. There is good amount of data available online for training number plate detectors. However, here's a problem - they do not work very well with Bangladeshi number plates; it's because Bangladeshi number plates are quite different from British, American, or even Indian ones. Images of Bangladeshi number plates are extremely limited on Google, and no dataset containing such images is publicly available. This calls for the need of creating a dataset containing photos of Bangladeshi number plates, which will be released publicly for free. This is intended to help everyone from beginners to machine learning to data scientists. Our work is intended to be primarily used for training neural networks.
To create a good dataset, the data needs to be diverse and distinguishable. Too similar data can be misleading to a neural network. Here ar