def _render_scene(self, camera, objects):
"""
Renders the window to 2D grayscale image
Called from render function for each viewpoint
"""
scene = vapory.Scene(camera=camera, objects=objects)
img = scene.render(width=self.render_size[0], height=self.render_size[1], quality=3)
img = rgb2gray(img)
return img
def _render_scene(self, camera, objects):
"""
Renders the window to 2D grayscale image
Called from render function for each viewpoint
"""
scene = vapory.Scene(camera=camera, objects=objects)
img = scene.render(width=self.render_size[0],
height=self.render_size[1],
quality=3)
img = rgb2gray(img)
return img
def _render_window_to2D(self):
"""
Renders the window to 2D black and white image
Called from render function for each viewpoint
"""
self.vtkrender_window.Render()
self.vtkwin_im = vtk.vtkWindowToImageFilter()
self.vtkwin_im.SetInput(self.vtkrender_window)
self.vtkwin_im.Update()
vtk_image = self.vtkwin_im.GetOutput()
height, width, _ = vtk_image.GetDimensions()
vtk_array = vtk_image.GetPointData().GetScalars()
components = vtk_array.GetNumberOfComponents()
arr = vtk_to_numpy(vtk_array).reshape(height, width, components)
arr = rgb2gray(arr)
return arr
def _render_window_to2D(self):
"""
Renders the window to 2D black and white image
Called from render function for each viewpoint
"""
self.vtkrender_window.Render()
self.vtkwin_im = vtk.vtkWindowToImageFilter()
self.vtkwin_im.SetInput(self.vtkrender_window)
self.vtkwin_im.Update()
vtk_image = self.vtkwin_im.GetOutput()
height, width, _ = vtk_image.GetDimensions()
vtk_array = vtk_image.GetPointData().GetScalars()
components = vtk_array.GetNumberOfComponents()
arr = vtk_to_numpy(vtk_array).reshape(height, width, components)
arr = rgb2gray(arr)
return arr
def _render_window_to2D(self, rgb=False):
"""
Renders the window to 2D grayscale image
Called from render function for each viewpoint
"""
self.vtkrender_window.Render()
self.vtkwin_im = vtk.vtkWindowToImageFilter()
self.vtkwin_im.SetInput(self.vtkrender_window)
self.vtkwin_im.Update()
vtk_image = self.vtkwin_im.GetOutput()
width, height, _ = vtk_image.GetDimensions()
vtk_array = vtk_image.GetPointData().GetScalars()
components = vtk_array.GetNumberOfComponents()
arr = vtk_to_numpy(vtk_array).reshape(height, width, components)
if rgb:
arr = arr.transpose([2, 1, 0])
else:
arr = rgb2gray(arr)
return arr
def _render_window_to2D(self, rgb=False):
"""
Renders the window to 2D grayscale image
Called from render function for each viewpoint
"""
self.vtkrender_window.Render()
self.vtkwin_im = vtk.vtkWindowToImageFilter()
self.vtkwin_im.SetInput(self.vtkrender_window)
self.vtkwin_im.Update()
vtk_image = self.vtkwin_im.GetOutput()
width, height, _ = vtk_image.GetDimensions()
vtk_array = vtk_image.GetPointData().GetScalars()
components = vtk_array.GetNumberOfComponents()
arr = vtk_to_numpy(vtk_array).reshape(height, width, components)
if rgb:
arr = arr.transpose([2, 1, 0])
else:
arr = rgb2gray(arr)
return arr
't1_cs_d1', 't1_cs_d2', 't2_ap_d1', 't2_ap_d2', 't2_mf_d1', 't2_mf_d2',
't2_rp_d1', 't2_rp_d2'
]
variations = [o + '_' + t for t in transformations for o in objects]
img_size = (100, 100)
output = np.zeros((90, np.prod(img_size)))
row_labels = []
i = 0
for obj in objects:
print(obj)
target_file = "{0:s}/{1:s}.png".format(stimuli_folder, obj)
target_img = misc.imread(target_file)
target_img = hlp.rgb2gray(target_img)
target_img = misc.imresize(target_img, img_size)
output[i, :] = np.ravel(target_img)
row_labels.append(obj)
i += 1
for obj in variations:
print(obj)
target_file = "{0:s}/{1:s}.png".format(stimuli_folder, obj)
target_img = misc.imread(target_file)
target_img = hlp.rgb2gray(target_img)
target_img = misc.imresize(target_img, img_size)
objects = ["o1", "o2", "o3", "o4", "o5", "o6", "o7", "o8", "o9", "o10"]
transformations = ["t1_cs_d1", "t1_cs_d2", "t2_ap_d1", "t2_ap_d2", "t2_mf_d1", "t2_mf_d2", "t2_rp_d1", "t2_rp_d2"]
variations = [o + "_" + t for t in transformations for o in objects]
img_size = (100, 100)
output = np.zeros((90, np.prod(img_size)))
row_labels = []
i = 0
for obj in objects:
print(obj)
target_file = "{0:s}/{1:s}.png".format(stimuli_folder, obj)
target_img = misc.imread(target_file)
target_img = hlp.rgb2gray(target_img)
target_img = misc.imresize(target_img, img_size)
output[i, :] = np.ravel(target_img)
row_labels.append(obj)
i += 1
for obj in variations:
print(obj)
target_file = "{0:s}/{1:s}.png".format(stimuli_folder, obj)
target_img = misc.imread(target_file)
target_img = hlp.rgb2gray(target_img)
target_img = misc.imresize(target_img, img_size)
