nailsonlinux

#! /usr/bin/env python
"""
Reads Darknet config and weights and creates Keras model with TF backend.

"""

import argparse
import configparser
import io
import os

nailsonlinux

import os
import asyncio
import aiobotocore
import io
from PIL import Image

AWS_ACCESS_KEY_ID = os.environ['AWS_ACCESS_KEY_ID']
AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY']

nailsonlinux

[MESSAGES CONTROL]
disable=C0114,C0115,C0116,E1101,E1133,R0903

nailsonlinux

import re

class Name:
    def __get__(self, obj, objtype=None):
        return self.value

    def __set__(self, obj, value):
        if len(value) > 20:
            raise ValueError("Name cannot exceed 20 characters.")
        self.value = value

nailsonlinux

# import the necessary packages
import numpy as np

def non_max_suppression(boxes, probs=None, overlapThresh=0.3):
	# if there are no boxes, return an empty list
	if len(boxes) == 0:
		return []

	# if the bounding boxes are integers, convert them to floats -- this
	# is important since we'll be doing a bunch of divisions

nailsonlinux

#!/bin/bash
# Flushing all rules
iptables -F FORWARD
iptables -F INPUT
iptables -F OUTPUT
iptables -X
# Setting default filter policy
iptables -P INPUT DROP
iptables -P OUTPUT DROP
iptables -P FORWARD DROP