tshanmukh

# importing copy as we have to copy the same image to different instances to visualize
import copy
plt.rcParams['figure.figsize'] = [14.0, 7.0]

# Set the parameters of the ORB algorithm by specifying the maximum number of keypoints to locate and
# the pyramid decimation ratio
orb = cv2.ORB_create(200, 2.0) # refer the opencv page for available arguments and usages

# computing the keypoints using the detectandcompute method, this accepts a grey scale image and None parameter
# is to let the ORB know we are not using any mask

diegopacheco

sudo apt-get install autoconf automake libtool curl make g++ unzip -y
git clone https://github.com/google/protobuf.git
cd protobuf
git submodule update --init --recursive
./autogen.sh
make
make check
sudo make install
sudo ldconfig

iandanforth

"""
Classic cart-pole system.

Pymunk version by Ian Danforth
"""

import math
import gym
import pygame
import pymunk

andreh7

mikedh

import pyglet
import pyglet.gl as gl

import numpy as np

import os
import tempfile
import subprocess
import collections

gboeing

To distribute a package on pypi

Directory structure

/project/
    /package/
        __init__.py
        module.py
 setup.py

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward