#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
import pkgutil

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)

egl = pkgutil.get_loader('eglRenderer')
if (egl):
	pybullet.loadPlugin(egl.get_filename(), "_eglRendererPlugin")
else:
	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(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()
