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class Node:
def __init__(self, element = None, next_node = None):
self._element = element
self._next = next_node
def get_element(self):
return self._element
def get_next(self):
return self._next
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8"/>
<title>Translate a Triangle</title>
<body onload="main()">
<canvas id="webgl" width="400" height="400">
Please use a browser that supports "canvas"
</canvas>
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8"/>
<title>Translate a Triangle</title>
<body onload="main()">
<canvas id="webgl" width="400" height="400">
Please use a browser that supports "canvas"
</canvas>
<!doctype html>
<html>
<body>
<canvas width = "570" height = "570" id = "my_Canvas"></canvas>
<script>
/*============== Creating a canvas ====================*/
var canvas = document.getElementById('my_Canvas');
gl = canvas.getContext('experimental-webgl');
@MinaGabriel
MinaGabriel / draw_points.html
Last active October 1, 2020 16:03
draw_points.html
<!doctype html>
<html>
<body>
<canvas width = "570" height = "570" id = "my_Canvas"></canvas>
<script>
/*================Creating a canvas=================*/
var canvas = document.getElementById('my_Canvas');
gl = canvas.getContext('experimental-webgl');
import time
from absl import app, flags, logging
from absl.flags import FLAGS
import cv2
import tensorflow as tf
from yolov3_tf2.models import (
YoloV3, YoloV3Tiny
)
from yolov3_tf2.dataset import transform_images
from yolov3_tf2.utils import draw_outputs
#! /usr/bin/env python
# coding=utf-8
# ================================================================
# Copyright (C) 2020 Mina Gabriel All rights reserved.
#
# Editor : PyCharm
# File name : preprocessing.py
# Author : Mina Gabriel
# Created date: 5/23/20 06:55
# Description :
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
#input image is 5 X 5 and 1 channel
input_shape = (1, 1, 5, 5)
tf.summary.trace_on(graph=True, profiler=True)
x = tf.random.normal(input_shape)
print(x.shape)
y = tf.keras.layers.Conv2D(
import os
from datetime import datetime
import coloredlogs, logging
import tensorflow as tf
import tensorflow.python.util.deprecation as deprecation
tf.debugging.set_log_device_placement(True)
coloredlogs.install()
import sys
from flask import Flask, jsonify, request
from keras.datasets import mnist
import MySQLdb
app = Flask(__name__)
@app.route("/", methods=["GET", "POST"])
def hello():