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# this Dockerfile is based on https://github.com/facebookresearch/DensePose/blob/master/docker/Dockerfile
FROM caffe2/caffe2:snapshot-py2-cuda9.0-cudnn7-ubuntu16.04

RUN mv /usr/local/caffe2 /usr/local/caffe2_build
ENV Caffe2_DIR /usr/local/caffe2_build

ENV PYTHONPATH /usr/local/caffe2_build:${PYTHONPATH}
ENV LD_LIBRARY_PATH /usr/local/caffe2_build/lib:${LD_LIBRARY_PATH}

RUN git clone https://github.com/facebookresearch/densepose /densepose

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from functools import partial

import numpy as np
from tqdm import tqdm

LUT_SIZE = 33

def _convert(pixel, lut):
    r, g, b = map(lambda x: round((x / 255) * LUT_SIZE - 1), pixel)
    idx = r + g * LUT_SIZE + b * (LUT_SIZE ** 2)

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from datetime import datetime
from itertools import product
from random import randint

import pandas as pd


def generate_df():
    # just example
    index = pd.date_range('2017-01-01', datetime.now(), freq='H')

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import logging
import pandas as pd
import requests

logging.basicConfig(level=logging.INFO,
                    format='%(asctime)s - %(levelname)s - %(message)s',
                    datefmt='%H:%M:%S', )
logger = logging.getLogger(__name__)

token = 'Bearer INSERT_YOUR_TOKEN_HERE'