mesutpiskin

#!/usr/bin/env python
# import the necessary packages
from __future__ import division
from scipy.spatial import distance as dist
import numpy as np
import time
import dlib
import cv2
from collections import OrderedDict

mesutpiskin

#!/usr/bin/env python
# import the necessary packages
from __future__ import division
from scipy.spatial import distance as dist
import numpy as np
import time
import dlib
import cv2
from collections import OrderedDict

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import numpy as np
import cv2
import glob

# Define the chess board rows and columns
CHECKERBOARD = (6,9)
subpix_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)
calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC + cv2.fisheye.CALIB_CHECK_COND + cv2.fisheye.CALIB_FIX_SKEW
objp = np.zeros((1, CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
objp[0,:,:2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)

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# -*- coding: utf-8 -*-
"""
Created on Sun Jun 17 19:59:33 2018

@author: mesut
"""
import yaml
import cv2
assert cv2.__version__[0] == '3', 'The fisheye module requires opencv version >= 3.0.0'
import numpy as np

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# http://mesutpiskin.com/blog/agirlikli-ortalama-oteleme-algoritmasi-mean-shift-ile-hareketli-nesne-takibi.html
# https://youtu.be/9qzaBzmmL7s

import cv2
import numpy as np


videoCapture = cv2.VideoCapture("video.mp4")

mesutpiskin

import os
from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
from PIL import Image
import glob



image_count = 5
current_dataset_folder = "train/*.*"
export_folder_name = "newdataset"

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using System.Collections.Generic;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;
using MongoDB.Driver;

namespace MyProject.Test
{
    public class DummyAsyncCursor<TEntity> : IAsyncCursor<TEntity>
    {

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apiVersion: v1
kind: Pod
metadata:
  name: bulkhead-myapp
spec:
  containers:
  - name: bulkhead-myapp-container
    image: bulkhead-myapp
    resources:
      requests:

mesutpiskin

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/go-redis/redis/v8"
)

mesutpiskin

Feature: Kullanıcılar e-tiracret platformu üzerinden seçtikleri ürünü satın alabilir.

    Scenario: (Success) Satın alınan ürününün stok miktarı, satın alınan adet kadar azalalır.      
        Given "USER1" kodlu kullanıcı oturum açmalıdır
        And "PRODUCT1" kodlu ürünün stok miktarı 100 olarak güncellenir
        And "USER1" kodlu kullanıcının sepeti temizlenir
        And "PRODUCT1" kodlu üründen sepete 1 adet eklenir

        When "USER1" kodlu kullanıcı ödeme işlemi gerçekleştirildiğinde