Inspired by dannyfritz/commit-message-emoji
See also gitmoji.
Commit type | Emoji |
---|---|
Initial commit | 🎉 :tada: |
Version tag | 🔖 :bookmark: |
New feature | ✨ :sparkles: |
Bugfix | 🐛 :bug: |
Inspired by dannyfritz/commit-message-emoji
See also gitmoji.
Commit type | Emoji |
---|---|
Initial commit | 🎉 :tada: |
Version tag | 🔖 :bookmark: |
New feature | ✨ :sparkles: |
Bugfix | 🐛 :bug: |
from __future__ import print_function | |
import requests | |
import json | |
import cv2 | |
addr = 'http://localhost:5000' | |
test_url = addr + '/api/test' | |
# prepare headers for http request | |
content_type = 'image/jpeg' |
import boto3 | |
from PIL import Image | |
from io import BytesIO | |
import os | |
class S3ImagesInvalidExtension(Exception): | |
pass | |
class S3ImagesUploadFailed(Exception): | |
pass |
# Support for Rspec / Capybara subdomain integration testing | |
# Make sure this file is required by spec_helper.rb | |
# (e.g. save as spec/support/subdomains.rb) | |
def switch_to_subdomain(subdomain) | |
# lvh.me always resolves to 127.0.0.1 | |
hostname = subdomain ? "#{subdomain}.lvh.me" : "lvh.me" | |
Capybara.app_host = "http://#{hostname}" | |
end |
"""Information Retrieval metrics | |
Useful Resources: | |
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt | |
http://www.nii.ac.jp/TechReports/05-014E.pdf | |
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf | |
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf | |
Learning to Rank for Information Retrieval (Tie-Yan Liu) | |
""" | |
import numpy as np |
=Navigating= | |
visit('/projects') | |
visit(post_comments_path(post)) | |
=Clicking links and buttons= | |
click_link('id-of-link') | |
click_link('Link Text') | |
click_button('Save') | |
click('Link Text') # Click either a link or a button | |
click('Button Value') |
'''This script goes along the blog post | |
"Building powerful image classification models using very little data" | |
from blog.keras.io. | |
It uses data that can be downloaded at: | |
https://www.kaggle.com/c/dogs-vs-cats/data | |
In our setup, we: | |
- created a data/ folder | |
- created train/ and validation/ subfolders inside data/ | |
- created cats/ and dogs/ subfolders inside train/ and validation/ | |
- put the cat pictures index 0-999 in data/train/cats |
from Crypto.Cipher import AES | |
from Crypto import Random | |
BS = 16 | |
pad = lambda s: s + (BS - len(s) % BS) * chr(BS - len(s) % BS) | |
unpad = lambda s : s[0:-ord(s[-1])] | |
class AESCipher: | |
def __init__( self, key ): | |
""" |
import warnings | |
from skimage.measure import compare_ssim | |
from skimage.transform import resize | |
from scipy.stats import wasserstein_distance | |
from scipy.misc import imsave | |
from scipy.ndimage import imread | |
import numpy as np | |
import cv2 | |
## |
# db/migrate/filename.rb | |
# generate with >> rails g model image alt:string hint:string file:string | |
class CreateImages < ActiveRecord::Migration[5.0] | |
def change | |
create_table :images do |t| | |
t.string :alt | |
t.string :hint | |
t.string :file |