public static List <Vector3> GetVertices(AugmentableObjectSample curr)
{
// compute the current candidate's bounding points
List <Vector3> BoundingBoxPoints = new List <Vector3>();
int x = 1, y = 1, z = 1;
for (int c = 0; c < 2; c++)
{
x = -x;
for (int j = 0; j < 2; j++)
{
y = -y;
for (int k = 0; k < 2; k++)
{
z = -z;
BoundingBoxPoints.Add(new Vector3(curr.location.X + x * curr.sizeMeters.X / 2,
curr.location.Y + y * curr.sizeMeters.Y / 2,
curr.location.Z + z * curr.sizeMeters.Z / 2));
}
}
}
return(BoundingBoxPoints);
}
// only returns the aug_object_samples and not the rbnn min vals!
public static List<AugmentableObjectSample> AugmentableSampleResultFormat(string augmentable_format_content)
{
// id position scale shape airplane_position distance_from_transitive_floor
// int x,y,z x,y,z BIRD x,y,z double
// space separated
List<AugmentableObjectSample> samples = new List<AugmentableObjectSample>();
string[] lines = augmentable_format_content.Split("\n");
foreach (var line in lines)
{
if (line.Length < 5)
continue;
string[] parts = line.Split(" ");
int id = int.Parse(parts[0]);
string[] pos_string = parts[1].Split(",");
Vector3 pos = new Vector3(float.Parse(pos_string[0]), float.Parse(pos_string[1]), float.Parse(pos_string[2]));
string[] scale_string = parts[2].Split(",");
Vector3 scale = new Vector3(float.Parse(scale_string[0]), float.Parse(scale_string[1]), float.Parse(scale_string[2]));
string name = parts[3];
AugmentableObjectSample samp = new AugmentableObjectSample(name, scale, pos, Numpy.MaxDimension(scale));
samples.Add(samp);
}
return samples;
}
public void UnfilteredSampleObjects(int ObjectsToAdd, Vector3 minWorldBound, Vector3 maxWorldBound)
{
this.minWorldBound = minWorldBound;
this.maxWorldBound = maxWorldBound;
for (int i = 0; i < 20 * ObjectsToAdd; i++)
{
AugmentableObjectSample curr = SampleObject();
samples.Add(curr);
}
}
public void ExecuteTest(string[] args)
{
string dmr = String.Join("\n", GenerateDmrGrid());
// write dmr
File.WriteAllText(Path.Combine(workdir, dmrfilename), dmr);
new CoreProcedure(Path.Combine(workdir, dmrfilename)).Dmr2Pcd();
for (int i = 0; i < 5000; i++)
{
Vector3 tmp = Vector3.Multiply((float)dimension, common.Numpy.RandomVector());
tmp = Vector3.Subtract(tmp,
new Vector3(0, 0, (float)dimension / 2.0f));
AugmentableObjectSample samp = new AugmentableObjectSample("BIRD", new Vector3(0.1f, 0.1f, 0.1f),
tmp,
5);
samples.Add(samp);
if (samp.location.Z > 0.0f)
{
solutions.Add(1);
}
else
{
solutions.Add(0);
}
}
// write augs
string serialized_augs = external_tools.common.PointCloudiaFormatSerializer.PointBoundingBoxAndMaxDimFormat(samples);
File.WriteAllText(Path.Combine(workdir, augsfilename), serialized_augs);
// write sols
File.WriteAllText(Path.Combine(workdir, "sols"), String.Join("\n", solutions));
List <int> predictions = UndergroundFilter.Execute(samples, Path.Combine(workdir, dmrfilename));
int[] preds = new int[samples.Count];
foreach (int p in predictions)
{
preds[p] = 1;
}
for (int i = 0; i < predictions.Count; i++)
{
if (preds[i] != solutions[i])
{
Console.WriteLine(preds[i] + " " + solutions[i]);
}
}
Console.ReadLine();
}
private int CreateNewPointsAndIndexThemBackIntoOriginalSamples(int nextIndex, List <Vector3> ToAdd, Dictionary <int, int> LidarPointIndexToSampleIndex)
{
for (int i = 0; i < samples.Count; i++)
{
AugmentableObjectSample curr = samples[i];
Vector3 location = samples[i].location;
List <Vector3> BoundingBoxPoints = BoundingBox.GetVertices(curr);
// add the bounding points both to be added and to keep track of what their object is, which indices belong to which object
for (int j = 0; j < BoundingBoxPoints.Count; j++)
{
ToAdd.Add(BoundingBoxPoints[j]);
LidarPointIndexToSampleIndex.Add(nextIndex++, i);
}
}
return(nextIndex);
}
