Krucamper

# install nestJs cli
npm install -g @nestjs/cli

# create new project nestJs 
nest new nestjs-tutorial 

# change to directory
cd nestjs-tutorial 

#run nestJs

Krucamper

npm install -g @nestjs/cli

Krucamper

<?php

namespace App\Console;

use Illuminate\Console\Scheduling\Schedule;
use Illuminate\Foundation\Console\Kernel as ConsoleKernel;

class Kernel extends ConsoleKernel
{
    /**

Krucamper

<?php

namespace App\Console\Commands;

use Illuminate\Console\Command;

class SendEmails extends Command
{
    /**
     * The name and signature of the console command.

Krucamper

Krucamper

from PIL import Image
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import model
import os

classes = {'BlackPanther', 'DoctorStrange', 'IronMan', 'ScarletWitch', 'SpiderMan', 'Thor'}
train_dir = 'raw'
logs_train_dir = './train_logs'

Krucamper

import os
import numpy as np
import tensorflow as tf
import input_data
import model

N_CLASSES = 6
IMG_W = 64
IMG_H = 64
BATCH_SIZE = 10

Krucamper

import tensorflow as tf

def inference(images, batch_size, n_classes):
    with tf.compat.v1.variable_scope('conv1') as scope:
        weights = tf.Variable(tf.random.truncated_normal(shape=[3, 3, 3, 64], stddev=1.0, dtype=tf.float32),
                              name='weights', dtype=tf.float32)

        biases = tf.Variable(tf.constant(value=0.1, dtype=tf.float32, shape=[64]),
                             name='biases', dtype=tf.float32)

Krucamper

import os
from PIL import Image
raw_image = './raw'
prepro_image = './genarate'
classes = {'BlackPanther', 'DoctorStrange', 'IronMan', 'ScarletWitch', 'SpiderMan', 'Thor'}

def genarate_image():
    for index, name in enumerate(classes):
        class_path = raw_image + "/" + name + "/"
        path_image = prepro_image +"/" + name +"/"

Krucamper