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import sys
import cv2

for img_path in all_image_path:
    one_img = cv2.imread(img_path, -1 | 128)
    if one_img == None:
        print(img_path, 'has problem, exit...')
        exit(-1)
    else:
        print(img_path, 'exists')

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def recover_from_pretrained(sess, net, ckpt_path=None, ckpt_step=-1, np_model_path=None):
    """
    recover from pretrained ckpt graph or numpy net parameters
    :param sess: the current session
    :param net: the feature tower
    :param ckpt_path: the ckpt root path (if there is any)
    :param ckpt_step: the ckpt step number (if there is any)
    :param np_model_path: the numpy model path (if there is any)
    :return: the correct step index for the current
    """

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#!/usr/bin/env python

# Copyright 2016, Tianwei Shen, HKUST.

"""
A handy script to execute a command recursively in a folder,
such as 'ls' or 'rm' files.
"""

import os

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# some bash tricks (Ubuntu 16.04)

## show the smallest 500 files
ll | awk '{print $5" "$NF}' | sort | head -500

## if find some empty files, you can output them to a file named empty_files.txt
## then rm them using this pipe
cat empty_files.txt | awk '{print "index/"$2}' | xargs rm

## rank file size from largest to smallest and show top 100

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#!/usr/bin/python

from PIL import Image
import math

test_image_list = '/home/tianwei/Data/sfm_data/test_image_list' # path to the image list
with open(test_image_list, 'r') as f:
    test_images = f.readlines()
    test_images = map(str.strip, test_images)