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# Run file -> python api.py
from fastapi import FastAPI # pip install fastapi
from haystack.document_store.elasticsearch import ElasticsearchDocumentStore
from haystack.retriever.dense import DensePassageRetriever
from haystack.reader.farm import FARMReader
from haystack.pipeline import ExtractiveQAPipeline

# initialize doc store, retriever and reader components
DOC_STORE = ElasticsearchDocumentStore(
    host='localhost', username='', password='', index='aurelius'

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# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: rgb_dl.proto

import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database

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import json
import trt_pose.coco
import torch
import torch2trt
from torch2trt import TRTModule
#import cv2
import torchvision.transforms as transforms
import PIL.Image
from trt_pose.parse_objects import ParseObjects
import os.path

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name: "oNet"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape: {
      dim: 1
      dim: 3
      dim: 48

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import argparse
# import logging
import sys
import time
import glob
# import os
# os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' 
# from tf_pose import common
import cv2
from tf_pose.estimator import TfPoseEstimator

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