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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):
View whammy.js
var vid = new Whammy.Video();
vid.add(canvas or data url)
window.Whammy = (function(){
// in this case, frames has a very specific meaning, which will be
// detailed once i finish writing the code
bigsnarfdude /
Created Aug 7, 2019
opencv convert to jpeg python of "webm" files
import cv2
cap = cv2.VideoCapture('test.webm')
ret, frame =
if ret == False:
View index.html
<!DOCTYPE html>
<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">
View client.js.html
<!DOCTYPE html>
<title>Hello world</title>
<script src = "/"></script>
var socket = io('http://localhost:8000');
import cv2
tracker = cv2.TrackerGOTURN_create()
# Read video
video = cv2.VideoCapture("chaplin.mp4")
# Exit if video not opened
if not video.isOpened():
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
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
bigsnarfdude /
Created Jul 9, 2019
tensorflowjs converter workflow from keras model
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
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