diff --git a/examples/pybullet/examples/testrender_egl.py b/examples/pybullet/examples/testrender_egl.py new file mode 100644 index 000000000..c4947f2b9 --- /dev/null +++ b/examples/pybullet/examples/testrender_egl.py @@ -0,0 +1,86 @@ +#using the eglRendererPlugin (hardware OpenGL acceleration) +#using EGL on Linux and default OpenGL window on Win32. + +#make sure to compile pybullet with PYBULLET_USE_NUMPY enabled +#otherwise use testrender.py (slower but compatible without numpy) +#you can also use GUI mode, for faster OpenGL rendering (instead of TinyRender CPU) + +import numpy as np +import matplotlib.pyplot as plt +import pybullet +import time + + +plt.ion() + +img = np.random.rand(200, 320) +#img = [tandard_normal((50,100)) +image = plt.imshow(img,interpolation='none',animated=True,label="blah") +ax = plt.gca() + +pybullet.connect(pybullet.DIRECT) + +pybullet.loadPlugin("eglRendererPlugin") +pybullet.loadURDF("plane.urdf",[0,0,-1]) +pybullet.loadURDF("r2d2.urdf") + +camTargetPos = [0,0,0] +cameraUp = [0,0,1] +cameraPos = [1,1,1] +pybullet.setGravity(0,0,-10) + +pitch = -10.0 + +roll=0 +upAxisIndex = 2 +camDistance = 4 +pixelWidth = 320 +pixelHeight = 200 +nearPlane = 0.01 +farPlane = 100 + +fov = 60 + +main_start = time.time() +while (1): + for yaw in range (0,360,10): + pybullet.stepSimulation() + start = time.time() + + viewMatrix = pybullet.computeViewMatrixFromYawPitchRoll(camTargetPos, camDistance, yaw, pitch, roll, upAxisIndex) + aspect = pixelWidth / pixelHeight; + projectionMatrix = pybullet.computeProjectionMatrixFOV(fov, aspect, nearPlane, farPlane); + img_arr = pybullet.getCameraImage(pixelWidth, pixelHeight, viewMatrix,projectionMatrix, shadow=1,lightDirection=[1,1,1],renderer=pybullet.ER_BULLET_HARDWARE_OPENGL) + stop = time.time() + print ("renderImage %f" % (stop - start)) + + w=img_arr[0] #width of the image, in pixels + h=img_arr[1] #height of the image, in pixels + rgb=img_arr[2] #color data RGB + dep=img_arr[3] #depth data + + print ('width = %d height = %d' % (w,h)) + + #note that sending the data to matplotlib is really slow + + #reshape is not needed + #np_img_arr = np.reshape(rgb, (h, w, 4)) + #np_img_arr = np_img_arr*(1./255.) + + #show + #plt.imshow(np_img_arr,interpolation='none',extent=(0,1600,0,1200)) + #image = plt.imshow(np_img_arr,interpolation='none',animated=True,label="blah") + + image.set_data(rgb)#np_img_arr) + ax.plot([0]) + #plt.draw() + #plt.show() + plt.pause(0.01) + #image.draw() + + +main_stop = time.time() + +print ("Total time %f" % (main_stop - main_start)) + +pybullet.resetSimulation()