Matt MattKovtun

MattKovtun / hash.py

Created October 31, 2018 14:07

Function for calculatin hash

	import hashlib, sys, os


	def calculate_hash(args):
	BUF_SIZE = 65536
	file_name = args[0]
	if not os.path.isfile(file_name):
	return "Not a file"

	sha1 = hashlib.sha1()

MattKovtun / main.js

Created July 26, 2018 13:04

	let model;

	const modelURL = 'http://localhost:5000/model';

	const preview = document.getElementById("preview");
	const predictButton = document.getElementById("predict");
	const clearButton = document.getElementById("clear");
	const numberOfFiles = document.getElementById("number-of-files");
	const fileInput = document.getElementById('file');

MattKovtun / main.js

Last active July 26, 2018 12:01

	let model;

	const modelURL = 'http://localhost:5000/model';

	const preview = document.getElementById("preview");
	const predictButton = document.getElementById("predict");
	const clearButton = document.getElementById("clear");
	const numberOfFiles = document.getElementById("number-of-files");
	const fileInput = document.getElementById('file');

MattKovtun / index.html

Last active July 26, 2018 11:53

	<body>
	<h1>TensorflowJS client side prediction</h1>
	<h2>When you first time press predict it will take more time, for model to load</h2>
	<main>
	<input type="file" id="file" multiple>
	<label for="file">Choose files</label>
	<button type="submit">Predict</button>
	<button type="submit">Clear</button>
	<span></span>
	</main>

MattKovtun / index.html

Created July 26, 2018 11:40

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title>TF JS example</title>
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]"></script>
	</head>
	<body>
	</body>
	</html>

MattKovtun / app.py

Last active July 18, 2018 11:06

	from flask_cors import CORS
	from flask import Flask, request, render_template, json, jsonify, send_from_directory
	import json
	import cv2
	import numpy as np
	import io

	app = Flask(__name__)
	CORS(app)

MattKovtun / main.js

Created July 18, 2018 10:45

	let model;

	const modelURL = 'http://localhost:5000/model';

	const preview = document.getElementById("preview");
	const predictButton = document.getElementById("predict");
	const clearButton = document.getElementById("clear");
	const numberOfFiles = document.getElementById("number-of-files");
	const fileInput = document.getElementById('file');

MattKovtun / index.html

Created July 18, 2018 10:18

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title>TF JS example</title>
	<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]"></script>
	<link rel="stylesheet" href="../static/frontend/styles.css">
	</head>
	<body>
	<h1 class="title">TensorflowJS client side prediction</h1>

MattKovtun / app.py

Last active July 18, 2018 10:02

	from flask_cors import CORS
	from flask import Flask, render_template

	app = Flask(__name__)
	CORS(app)


	@app.route("/", methods=["GET"])
	def main():
	return render_template('index.html')

MattKovtun / train_model.py

Last active July 18, 2018 10:41

	# Your training happens here
	# Hundreds and hundreds of layers
	# Stacked to create the greatest model ever


	# don't forget saving to json format
	import tensorflowjs as tfjs
	tfjs.converters.save_keras_model(model, "model_js")