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kafka-topics.sh --list --zookeeper localhost:2181


kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic status

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docker stop kafka-server && docker rm kafka-server
docker stop zookeeper-server && docker rm zookeeper-server

docker run -d --name zookeeper-server --network host -e ALLOW_ANONYMOUS_LOGIN=yes bitnami/zookeeper:latest

docker run -d --name kafka-server --network host -e ALLOW_PLAINTEXT_LISTENER=yes -e KAFKA_CFG_ZOOKEEPER_CONNECT=localhost:2181 bitnami/kafka:latest

HassankSalim

rosbag info --yaml --key=types[0].type 2020-07-15-11-29-48.bag 

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select * from pg_stat_activity where (state = 'idle in transaction') and xact_start is not null;

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import requests
import time
import json
import re

root_url = "http://192.168.0.1"
base_url = root_url + "/cgi"
login_url = base_url + "/login"
get_busy_url = base_url + "/getBusy"

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import re

# Custom grep
grep = lambda lib, regex : filter(lambda x : re.search(regex, x), dir(lib))

# Usage
# input: list(grep(bson, 'deco'))
# result: ['_utf_8_decode', 'decode_all', 'decode_file_iter', 'decode_iter']
# input: list(grep(numpy, '^a.*y$'))
# result: ['any', 'array', 'asanyarray', 'asarray', 'ascontiguousarray', 'asfarray', 'asfortranarray']

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import numpy as np
import cv2
import os
import random
import pandas as pd
import sys

class ImageDataLoader():
    def __init__(self, data_path, gt_path, shuffle=False, gt_downsample=False, pre_load=False, num_classes=10):
        #pre_load: if true, all training and validation images are loaded into CPU RAM for faster processing.

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#!/usr/bin/env python2
# -*- coding: utf-8 -*-


import torch
import torch.nn as nn
import torch.nn.functional as F
from src.network import Conv2d, FC

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import torch
import torch.nn as nn
import torch.nn.functional as F

import src.network as network
from src.models import CMTL

class CrowdCounter(nn.Module):
    def __init__(self, ce_weights=None):
        super(CrowdCounter, self).__init__()        

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import os
import torch
import numpy as np
from src.crowd_count import CrowdCounter
from src import network
from src.data_loader import ImageDataLoader
from src import utils


torch.backends.cudnn.enabled = True