Jojozzc

import os, sys
curPath = os.path.abspath(os.path.dirname(__file__))
rootPath = os.path.split(curPath)[0]
print('rootPath:{}'.format(rootPath))
sys.path.append(rootPath)

Jojozzc

def interval_peek(arr):
    '''
    Find all no-zero continuous interval, then in every interval, set all element 0 except the peek.
    :param arr:
    :return:
    '''
    left = 0
    arr_len = len(arr)
    res = arr[:]
    while left < arr_len:

Jojozzc

def rgb2gray(img):
    assert np.ndim(img) == 3
    img = color.rgb2gray(img) * 255
    img = np.uint8(img)
    return img

Jojozzc

import pandas as pd
import numpy as np

def load_train_data(path='inputFiles/train.csv'):
    x = []
    y = []
    data = pd.read_csv(path)
    data = data.values
    data_num = len(data)
    for i in range(0, data_num):

Jojozzc

import re
def is_img_file(file_name):
    file_name = str(file_name)
    file_name = file_name.lower()
    return re.search('\.bmp$', file_name) or re.search('\.png$', file_name) or \
            re.search('\.jpg$', file_name) or re.search('\.jpeg', file_name) or re.search('\.tiff', file_name)

Jojozzc

def cal_IoU(img, lab, nb_class):
    for i in range(nb_class):
        mask1 = (img == (i + 1)).astype('uint8')
        mask2 = (lab == (i + 1)).astype('uint8')
        mask_and = cv2.bitwise_and(mask1, mask2)
        mask_or = cv2.bitwise_or(mask1, mask2)

        s1 = np.sum(mask_and)
        s2 = np.sum(mask_or)

Jojozzc

# Usage:
# $python file_count.py [option]
# options:
# -r      count recursively
# -s[dir] workdir
# eg.
# #work on curent workdir:
# $python file_count.py
# #count recursively

Jojozzc

import os
# GPU 00000000:88:00.0
#    FB Memory Usage
#        Total                       : 8119 MiB
#        Used                        : 2 MiB
#        Free                        : 8117 MiB
#    BAR1 Memory Usage
#        Total                       : 256 MiB
#        Used                        : 5 MiB
#        Free                        : 251 MiB

Jojozzc

import matplotlib.pyplot as plt
import numpy as np

def show_images(images, cols = 1, titles = None):
    """Display a list of images in a single figure with matplotlib.
    
    Parameters
    ---------
    images: List of np.arrays compatible with plt.imshow.
    

Jojozzc

def cvt_unix_like_path(path):
    if path is None:
        return None
    path = str(path)
    unix_p_temp = path.replace('\\', '/')
    unix_p = ''
    pre = ''
    for ch in unix_p_temp:
        if not (ch == '/'):
            unix_p = unix_p + ch