cheadrian

import glob
import os
import time

import torch
from PIL import Image
from vizer.draw import draw_boxes

import cv2

cheadrian

#Note: this solution dosen't guarantee that your network will work as expected after you convert with this, 
#because it wasn't tested 
#enought 

#Environement: tensorflow 1.14.0

# Lint as: python2, python3
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");

cheadrian

from collections import OrderedDict

from torch import nn
from torch.nn import functional as F


class _SimpleSegmentationModel(nn.Module):
    __constants__ = ['aux_classifier']

    def __init__(self, backbone, classifier, aux_classifier=None, export_onnx=False):

cheadrian

import fitz
import tkinter as tk
from tkinter import ttk
from tkinter import *
from tkinter import filedialog
from tkinterdnd2 import DND_FILES, TkinterDnD

def on_drop(file_path):
    # Split multiple files:
    paths = file_path.split(' ')

cheadrian

These are the flows witch you can import into your Node-RED.

Contains OpenAI API examples for ChatGPT and Dall-e 2 combined with chat platforms, like Messenger, Whatsapp Business, Whatsapp Personal and Telegram.

There's also an example with email conversation.

You can find the list of articles which you can use with these files on Medium, here.

cheadrian

import numpy as np 
from collections import namedtuple, deque
from itertools import count 
import random, datetime, os, copy, glob, math, time, asyncio, base64, shutil

import cv2 

import gym, ray
from gym import Env, spaces
from gym.spaces import Box

cheadrian

For Manifest V3

https://gist.github.com/cheadrian/8424217dda5a28724f290eef7fb4e059

or

https://www.youtube.com/watch?v=UjH2INUPmF4

Example bellow works only for Chrome Extension Manifest V2

cheadrian

import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider

def sobel_edge_detector(img, threshold=50):
    grad_x = cv.Sobel(img, cv.CV_64F, 1, 0)
    grad_y = cv.Sobel(img, cv.CV_64F, 0, 1)
    grad = np.sqrt(grad_x**2 + grad_y**2)
    grad_norm = (grad * 255 / grad.max()).astype(np.uint8)

cheadrian

/*
 * Check the Snack demo here:
 * https://snack.expo.dev/@cheadrian/custom-scroll-view-indicator-with-reanimated-and-gesture
 * Article with gif and features:
 * https://che-adrian.medium.com/b78b238067b3?source=friends_link&sk=66df3163984fbcacbf9f7f4193b92e25
 */

import { useEffect, useRef, useState } from 'react';
import { View, StyleSheet } from 'react-native';
import { ScrollView } from 'react-native-gesture-handler';

cheadrian

/*
 * Forward data received by webhook from Google Ads Form Extension 
 * to selected email
 * Details at:
 * https://che-adrian.medium.com/create-a-webhook-for-google-ads-lead-form-extension-using-wordpress-and-wp-webhooks-plugin-and-cd2a3c7fb1c3
 */
add_filter( 'wpwhpro/run/actions/custom_action/return_args', 'wpwh_ads_email', 10, 3 );
function wpwh_ads_email( $return_args, $identifier, $response_body ){
    //Email where you receive the data
    $to = "example@example.com";