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#pragma once
#include "NVSceneCapturerUtils.generated.h"

USTRUCT(BlueprintType)
struct FCapturedObjectData
{
	GENERATED_USTRUCT_BODY()

public:   
    UPROPERTY(EditAnywhere, BlueprintReadWrite)

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#pragma once
#include "NVSceneCapturerModule.h"
#include "Components/ActorComponent.h"
#include "Components/StaticMeshComponent.h"
#include "IImageWrapper.h"
#include "Runtime/Core/Public/Misc/FileHelper.h"
#include "Kismet/BlueprintFunctionLibrary.h"
#include "Serialization/JsonSerializerMacros.h"
#include "Serialization/JsonTypes.h"
#include "Paths.h"

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{

  "SettingsVersion": 1.0,

  "SimMode": "UrdfBot",

  "LocalHostIp": "127.0.0.1",

  "ViewMode": "GroundObserver",

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/*
* Copyright (c) 2018 NVIDIA Corporation.  All rights reserved.        
* This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0
* International License.  (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)
*/

#pragma once

#include "DomainRandomizationDNNPCH.h"
#include "RandomComponentBase.h"

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"""
This script will demonstrate how to use a pretrained model, in PyTorch, 
to make predictions. Specifically, we will be using VGG16 with a cat 
image.

References used to make this script:
PyTorch pretrained models doc:
    http://pytorch.org/docs/master/torchvision/models.html
PyTorch image transforms example:
    http://pytorch.org/tutorials/beginner/data_loading_tutorial.html#transforms

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# returns the list of subexpressions which a given tape depends on directly
function list_subexpressions(nd::Vector{NodeData})

    # TODO: code overlap with compute_gradient_sparsity
    indices = Set{Int}()
    for k in 1:length(nd)
        nod = nd[k]
        if nod.nodetype == SUBEXPRESSION

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<?xml version="1.0" ?>
<launch>
  <arg name="paused" default="false"/>
  <arg name="use_sim_time" default="true"/>
  <arg name="gui" default="true"/>
  <arg name="headless" default="false"/>
  <arg name="debug" default="false"/>
  <arg name="verbose" default="false"/>
  <arg name="world_name" default="worlds/empty.world"/> <!-- Note: the world_name is with respect to GAZEBO_RESOURCE_PATH environmental variable -->

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   pa = Vpara(x_min=x_min,x_max=x_max,y_min=y_min,y_max=y_max,sm=0.01);

 @NLconstraint(mdl, obs_con[j=1:Q,i=2:N+1], 1 <= ((x[i]-X_obs[j,i])^2)/((a[j]+sm)^2) + ((y[i]-Y_obs[j,i])^2)/((b[j]+sm)^2))

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Pkg.clone("https://github.com/huckl3b3rry87/PrettyPlots.jl")

Pkg.clone("https://github.com/huckl3b3rry87/VehicleModels.jl")

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module DiffEqProblemLibrary

using DiffEqBase, ParameterizedFunctions,
      FiniteElementDiffEq, AlgebraicDiffEq, JLD
print("1")
include("ode_premade_problems.jl")
print("2")
include("dae_premade_problems.jl")
print("3")
include("sde_premade_problems.jl")