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# Fast reading from the raspberry camera with Python, Numpy, and OpenCV
# Allows to process grayscale video up to 124 FPS (tested in Raspberry Zero Wifi with V2.1 camera)
#
# Made by @CarlosGS in May 2017
# Club de Robotica - Universidad Autonoma de Madrid
# http://crm.ii.uam.es/
# License: Public Domain, attribution appreciated

import cv2
import numpy as np

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# from : https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/graph_editor/examples/edit_graph_example.py
import numpy as np

import tensorflow as tf
from tensorflow.contrib import graph_editor as ge

# create a graph
g = tf.Graph()

with g.as_default():

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def ransac_polyfit(x, y, order=3, n=20, k=100, t=0.1, d=100, f=0.8):
  # Thanks https://en.wikipedia.org/wiki/Random_sample_consensus
  
  # n – minimum number of data points required to fit the model
  # k – maximum number of iterations allowed in the algorithm
  # t – threshold value to determine when a data point fits a model
  # d – number of close data points required to assert that a model fits well to data
  # f – fraction of close data points required
  
  besterr = np.inf

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## Delete a remote branch
$ git push origin --delete <branch> # Git version 1.7.0 or newer 
$ git push origin :<branch> # Git versions older than 1.7.0

## Delete a local branch
$ git branch --delete <branch>
$ git branch -d <branch> # Shorter version
$ git branch -D <branch> # Force delete un-merged branches

## Delete a local remote-tracking branch

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import http.server
import cgi
import base64
import json
from urllib.parse import urlparse, parse_qs


class CustomServerHandler(http.server.BaseHTTPRequestHandler):

    def do_HEAD(self):

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#include <IRremote.h>

/*

 Send infrared commands from the Arduino to the iRobot Roomba
 by probono
 
 2013-03-17 Initial release
 

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