71 lines
1.9 KiB
Python
71 lines
1.9 KiB
Python
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#make sure to compile pybullet with PYBULLET_USE_NUMPY enabled
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#otherwise use testrender.py (slower but compatible without numpy)
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#you can also use GUI mode, for faster OpenGL rendering (instead of TinyRender CPU)
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import numpy as np
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import matplotlib.pyplot as plt
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import pybullet
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import time
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from pylab import *
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ion()
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img = standard_normal((50,100))
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image = imshow(img,interpolation='none',animated=True,label="blah")
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#pybullet.connect(pybullet.GUI)
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pybullet.connect(pybullet.DIRECT)
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pybullet.loadURDF("plane.urdf",[0,0,-1])
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pybullet.loadURDF("r2d2.urdf")
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camTargetPos = [0,0,0]
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cameraUp = [0,0,1]
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cameraPos = [1,1,1]
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pitch = -10.0
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roll=0
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upAxisIndex = 2
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camDistance = 4
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pixelWidth = 320
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pixelHeight = 200
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nearPlane = 0.01
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farPlane = 100
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fov = 60
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main_start = time.time()
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while (1):
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for yaw in range (0,360,10):
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start = time.time()
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viewMatrix = pybullet.computeViewMatrixFromYawPitchRoll(camTargetPos, camDistance, yaw, pitch, roll, upAxisIndex)
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aspect = pixelWidth / pixelHeight;
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projectionMatrix = pybullet.computeProjectionMatrixFOV(fov, aspect, nearPlane, farPlane);
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img_arr = pybullet.getCameraImage(pixelWidth, pixelHeight, viewMatrix,projectionMatrix, shadow=1,lightDirection=[1,1,1],renderer=pybullet.ER_BULLET_HARDWARE_OPENGL)
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stop = time.time()
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print ("renderImage %f" % (stop - start))
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w=img_arr[0] #width of the image, in pixels
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h=img_arr[1] #height of the image, in pixels
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rgb=img_arr[2] #color data RGB
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dep=img_arr[3] #depth data
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print ('width = %d height = %d' % (w,h))
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#note that sending the data to matplotlib is really slow
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np_img_arr = np.reshape(rgb, (h, w, 4))
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np_img_arr = np_img_arr*(1./255.)
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#show
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#plt.imshow(np_img_arr,interpolation='none',extent=(0,1600,0,1200))
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image.set_data(np_img_arr)
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#draw()
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plt.pause(0.0001)
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main_stop = time.time()
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print ("Total time %f" % (main_stop - main_start))
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pybullet.resetSimulation()
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