comtom

from PIL import Image


def resize_and_crop(img, size=(255, 255)):
    img = Image.open(img)
    img_ratio = img.size[0] / img.size[1]
    ratio = size[0] / size[1]

    if ratio > img_ratio:
        img = img.resize((size[0], int(size[0] * img.size[1] / img.size[0])),

comtom

import os

import cv2
import numpy as np
from tensorflow.python.keras.preprocessing.image import load_img, img_to_array
from tensorflow.python.keras.models import load_model
from resize import resize_and_crop

width, height = 224, 224
dimension = f'{ width }px'

comtom

import sys

from predict import predict


def make_predictions(filename):
    result = []
    for i in range(3):
        result.append(predict(filename, model=i))

comtom

# -*- coding: utf-8 -*-
"""Modelo_Acc+80.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1kLQn4QbQKLGSHXhAsmKrIMBcKLWHNWvg
"""

import matplotlib

comtom

<?php
$active_group = 'default';
$query_builder = TRUE;
$db['default'] = array(
 'dsn' => '',
 'hostname' => 'database.host.local',
 'username' => 'username',
 'password' => 'hackme',
 'database' => 'database_name',
 'dbdriver' => 'pdo',

comtom

func returnsError() error {
	if bad() {
		return ErrBad
	}
	return nil
}

comtom

func returnsError() error {
	var p *MyError = nil
	if bad() {
		p = ErrBad
	}
	return p // Will always return a non-nil error.
}

comtom

package main
import "fmt"

func main() {
    messages := make(chan string)
    signals := make(chan bool)
   select {
    case msg := <-messages:
        fmt.Println("received message", msg)

comtom

#!/bin/bash
go test -cpuprofile cpu.prof -memprofile mem.prof -bench .
pprof -http=:6060 -alloc_objects mem.prof
pprof -http=:6060 cpu.prof 

comtom

import "golang.org/x/sync/errgroup"
...
g, ctx := errgroup.WithContext(ctx)
complete := make(chan []Store, len(locations))

for _, location := range locations {
  g.Go(fetchStores(ctx, store.Id, complete))
}
if err := g.Wait(); err != nil {
  log.Errorf("%s", err)