Lucs1590

# Pythono3 code to rename multiple
import os
import glob


def main():
    caminho = "path/to/archives/"

    for i, arquivo in enumerate(glob.glob(os.path.join(caminho, "*.jpg"))):
        new_file = caminho + "name" + str(i) + ".jpg"

Lucs1590

#include "DHT.h"
#define DHTPIN 14 
#define DHTTYPE DHT11 
const int pino_sinal_analogico = 25;
DHT dht(DHTPIN, DHTTYPE);
float localHum = 0;
float localTemp = 0;
float percentUm = 0;
int valor_analogico ;

Lucs1590

# pixels_per_metric = tamanho objeto em px / tamanho real
from scipy.spatial import distance as dist
from imutils import perspective
from imutils import contours
import numpy as np
import argparse
import imutils
import cv2

Lucs1590

import cv2
import numpy as np
import utils as ut
from matplotlib import pyplot as plt

img = '/home/brito/Documentos/Dev/tcc/img/f1.jpeg'
img = cv2.imread(img)
mask = np.zeros(img.shape[:2],np.uint8)

bgdModel = np.zeros((1,65),np.float64)

Lucs1590

def gerar_nos(seq, arr= []):
    seq = list(seq)
    saida_array = seq[:3]
    arr.append(''.join(saida_array))
    if len(seq) == 3:
        return arr
    seq.pop(0)
    return gerar_nos(seq)

Lucs1590

__author__ = 'sidharthgoyal'
import math

increment = 0.1
startingPoint = [1, 1]
point1 = [1,5]
point2 = [6,4]
point3 = [5,2]
point4 = [2,1]

Lucs1590

import sklearn.datasets as datasets
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.externals.six import StringIO
from IPython.display import Image
from sklearn.tree import export_graphviz
import pydotplus

iris = datasets.load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)

Lucs1590

import os
import glob
import pandas as pd

def main():
    data = pd.read_csv('/path/of/txt/', sep=" ", header=None)[0].values.tolist()
    caminho = "/path/of/files"
    finded = 0
    deleted = 0
    

Lucs1590

from nkocr import OcrTable

text = OcrTable("paste_image_url_here")
print(text) # or print(text.text)

Lucs1590

def remove_lines(image, colors):
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    bin_image = cv2.threshold(
        gray_image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

    h_contours = get_contours(bin_image, (25, 1))
    v_contours = get_contours(bin_image, (1, 25))

    for contour in h_contours:
        cv2.drawContours(image, [contour], -1, colors[0][0], 2)