BigsnarfDude bigsnarfdude

## gist:132732d1fc6a1f343f9bcd420f265d03
https://github.com/tensorflow/tfjs/issues/822

## extractor.py
from slimit.parser import Parser
from slimit.visitors import nodevisitor
from slimit import ast
import re


def check_code_sanity(sequence):
    parser = Parser()
    tree = parser.parse(sequence)
    for node in nodevisitor.visit(tree):

## whammy.js
/*
	var vid = new Whammy.Video();
	vid.add(canvas or data url)
	vid.compile()
*/

window.Whammy = (function(){
	// in this case, frames has a very specific meaning, which will be
	// detailed once i finish writing the code

## tester.py
import cv2

cap = cv2.VideoCapture('test.webm')

i=0
while(cap.isOpened()):
    ret, frame = cap.read()
    if ret == False:
        break
    cv2.imwrite('tester'+str(i)+'.jpg',frame)

## index.html
<!DOCTYPE html>
<html>
<head>

    <meta charset="utf-8">
    <meta name="description" content="WebRTC code samples">
    <meta name="viewport" content="width=device-width, user-scalable=yes, initial-scale=1, maximum-scale=1">
    <meta itemprop="description" content="Client-side WebRTC code samples">
    <meta itemprop="image" content="../../../images/webrtc-icon-192x192.png">
    <meta itemprop="name" content="WebRTC code samples">

## client.js.html
<!DOCTYPE html>
<html>
   <head>
      <title>Hello world</title>
   </head>
   <script src = "/socket.io/socket.io.js"></script>

   <script>
      var socket = io('http://localhost:8000');
      socket.emit('clientEvent',

## goturn_opencv_tracker.py
import cv2


tracker = cv2.TrackerGOTURN_create()

# Read video
video = cv2.VideoCapture("chaplin.mp4")

# Exit if video not opened
if not video.isOpened():

## webcam_yolo_car_counter.py
import sys
import cv2
from trackers.tracker import create_blob, add_new_blobs, remove_duplicates
import numpy as np
from collections import OrderedDict
from detectors.detector import get_bounding_boxes
import uuid
import os
import contextlib
from datetime import datetime

## single_plate_tensorflow.py
import argparse
import time
import cv2
import numpy as np
import tensorflow as tf
from imutils import paths
from object_detection.utils import label_map_util
from base2designs.plates.plateFinder import PlateFinder
from base2designs.plates.predicter import Predicter
from base2designs.plates.plateDisplay import PlateDisplay

## train.py
from __future__ import absolute_import, division, print_function, unicode_literals

# TensorFlow and tf.keras
import tensorflow as tf
from tensorflow import keras

# Helper libraries
import numpy as np
import matplotlib.pyplot as plt