Add ploting to VisualISAM2Example.py
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46a1970731
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@ -1,5 +1,100 @@
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import gtsam
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from gtsam.examples.SFMdata import *
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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import time # for sleep()
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def plotPoint3(fignum, point, linespec):
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fig = plt.figure(fignum)
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ax = fig.gca(projection='3d')
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ax.plot([point.x()],[point.y()],[point.z()], linespec)
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def plot3DPoints(fignum, values, linespec, marginals=None):
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# PLOT3DPOINTS Plots the Point3's in a values, with optional covariances
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# Finds all the Point3 objects in the given Values object and plots them.
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# If a Marginals object is given, this function will also plot marginal
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# covariance ellipses for each point.
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keys = values.keys()
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# Plot points and covariance matrices
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for key in keys:
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try:
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p = values.point3_at(key);
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# if haveMarginals
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# P = marginals.marginalCovariance(key);
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# gtsam.plotPoint3(p, linespec, P);
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# else
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plotPoint3(fignum, p, linespec);
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except RuntimeError:
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continue
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#I guess it's not a Point3
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def plotPose3(fignum, pose, axisLength=0.1):
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# get figure object
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fig = plt.figure(fignum)
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ax = fig.gca(projection='3d')
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# get rotation and translation (center)
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gRp = pose.rotation().matrix() # rotation from pose to global
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C = pose.translation().vector()
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# draw the camera axes
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xAxis = C+gRp[:,0]*axisLength
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L = np.append(C[np.newaxis], xAxis[np.newaxis], axis=0)
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ax.plot(L[:,0],L[:,1],L[:,2],'r-')
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yAxis = C+gRp[:,1]*axisLength
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L = np.append(C[np.newaxis], yAxis[np.newaxis], axis=0)
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ax.plot(L[:,0],L[:,1],L[:,2],'g-')
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zAxis = C+gRp[:,2]*axisLength
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L = np.append(C[np.newaxis], zAxis[np.newaxis], axis=0)
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ax.plot(L[:,0],L[:,1],L[:,2],'b-')
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# # plot the covariance
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# if (nargin>2) && (~isempty(P))
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# pPp = P(4:6,4:6); % covariance matrix in pose coordinate frame
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# gPp = gRp*pPp*gRp'; % convert the covariance matrix to global coordinate frame
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# gtsam.covarianceEllipse3D(C,gPp);
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# end
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def visual_ISAM2_plot(poses, points, result):
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# VisualISAMPlot plots current state of ISAM2 object
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# Author: Ellon Paiva
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# Based on MATLAB version by: Duy Nguyen Ta and Frank Dellaert
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# Declare an id for the figure
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fignum = 0;
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fig = plt.figure(fignum)
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ax = fig.gca(projection='3d')
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plt.cla()
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# Plot points
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# Can't use data because current frame might not see all points
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# marginals = Marginals(isam.getFactorsUnsafe(), isam.calculateEstimate()); # TODO - this is slow
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# gtsam.plot3DPoints(result, [], marginals);
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plot3DPoints(fignum, result, 'rx');
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# Plot cameras
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M = 0;
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while result.exists(int(gtsam.Symbol('x',M))):
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ii = int(gtsam.Symbol('x',M));
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pose_i = result.pose3_at(ii);
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plotPose3(fignum, pose_i, 10);
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M = M + 1;
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# draw
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ax.set_xlim3d(-40, 40)
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ax.set_ylim3d(-40, 40)
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ax.set_zlim3d(-40, 40)
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plt.show(block=False)
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plt.draw();
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def visual_ISAM2_example():
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# Define the camera calibration parameters
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@ -76,7 +171,8 @@ def visual_ISAM2_example():
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print gtsam.Symbol('l',j)
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print currentEstimate.point3_at(int(gtsam.Symbol('l',j)))
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# TODO: Print to screen or plot using matplotlib
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visual_ISAM2_plot(poses, points, currentEstimate);
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time.sleep(1)
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# Clear the factor graph and values for the next iteration
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graph.resize(0);
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