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import detectron2
from detectron2.utils.logger import setup_logger
setup_logger()

# import some common libraries
import numpy as np
import cv2
import random
import datetime

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# -*- coding: utf-8 -*-

import simplekml
import os
from itertools import islice

def kml_converter(inputfile,kml):
    f = open(inputfile,"r")
    for row in islice(f,1,None):  #skip read header
        data=row.split(",")

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import matplotlib.pyplot as plt
from matplotlib.pyplot import figure

figure(num=None, figsize=(45, 6), dpi=80, facecolor='w', edgecolor='k')

def process(mypath):
    cols = []
    xlist=[]
    f= open(mypath,"r")
    lines = f.readlines()

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import cv2
import numpy as np
import os
import sys

argc = len(sys.argv)
border = 2
basePath = "output_networks/pothole/"
if argc > 1:
    srcName = sys.argv[1]

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#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/opencv.hpp>
#include <tesseract/baseapi.h>
#include <leptonica/allheaders.h>

std::string extractIntegerFromString(string str)
{
	std::string result;
	std::stringstream ss;

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int slider_max, slider, displayHeight;
int displayWidth = 1900;
Mat src1;
Mat dst;
cv::Rect roi;

static void on_trackbar(int, void*)
{
	roi = cv::Rect(slider, 0, displayWidth, displayHeight);
	dst = src1(roi);

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# Inference in Caffe2 using the ONNX model
import caffe2.python.onnx.backend as backend
import onnx
import torch
import torchvision
from torchvision.transforms import transforms
from PIL import Image
import numpy as np
 
# First load the onnx model

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import os
import pandas as pd

data_folders = next(os.walk('.'))[1]

filenames = [os.listdir(f) for f in data_folders]
test_ratio = 10

files_dict = dict(zip(data_folders, filenames))
base_gcs_path = 'gs://v26/v26-30kinds-augmented-color/'

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JetsonTX2 YOLOv3 TENSOR-RT

Untar : https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps/releases/tag/DS2
Edit deepstream_reference_apps-DS2/Makefile.config
 - CUDA_VER:=9.0
 - PLATFORM:=TEGRA
go to sources/apps/trt-yolo , then sudo make && sudo make install
copy trt-yolo-app to deepstream_reference_apps-DS2/trt-yolo-app
download all files from https://github.com/NVIDIA-AI-IOT/deepstream_reference_apps/blob/master/yolo/prebuild.sh to data/
edit data/test_images.txt 

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import os
from os import walk, getcwd

input_list = []
for file in os.listdir("/home/ivan/darknet/data/objdamage/"):
    input_list.append(file)

for filename in input_list:
    content = open("/home/ivan/darknet/data/objdamage/"+filename, "r")