def save_mesh_to_file(mesh):
# Get the file name (excluding extension) from the input image path
filename = os.path.splitext(os.path.basename(file.get_image_path()))[0]
mesh.save(file.output_path + filename + '.stl')
level=threshold,
spacing=(1., 1., 1.),
gradient_direction='descent')
# Export the mesh as stl
mymesh = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
for i, f in enumerate(faces):
for j in range(3):
mymesh.vectors[i][j] = verts[f[j], :]
file_utils.save_mesh_to_file(imageurl, mymesh)
def ChangeContrast(self, gamma=1.0):
"""
change contrast of an image
gamma value 1 for same image
gamma value greater than 1 to increase brightness
gamma value less than 1 to make image darker
"""
invGamma = 1.0 / gamma
table = np.array([((i / 255.0)**invGamma) * 255
for i in np.arange(0, 256)]).astype("uint8")
# apply gamma correction using the lookup table
return cv2.LUT(self.im, table)
if __name__ == "__main__":
convertHatchedImageToSTL(file.get_image_path())
Contour value to search for isosurfaces in `volume`. If not
given or None, the average of the min and max of vol is used.
spacing : length-3 tuple of floats
Voxel spacing in spatial dimensions corresponding to numpy array
indexing dimensions (M, N, P) as in `volume`.
gradient_direction : string
Controls if the mesh was generated from an isosurface with gradient
descent toward objects of interest (the default), or the opposite.
The two options are:
* descent : Object was greater than exterior
* ascent : Exterior was greater than object
'''
verts, faces, normals, values = measure.marching_cubes_lewiner(
volume=voxel,
level=threshold,
spacing=(1., 1., 1.),
gradient_direction='descent')
# Export the mesh as stl
mymesh = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
for i, f in enumerate(faces):
for j in range(3):
mymesh.vectors[i][j] = verts[f[j], :]
file_utils.save_mesh_to_file(imageurl, mymesh)
if __name__ == "__main__":
convertGrayScaleToSTL(file.get_image_path())
Contour value to search for isosurfaces in `volume`. If not
given or None, the average of the min and max of vol is used.
spacing : length-3 tuple of floats
Voxel spacing in spatial dimensions corresponding to numpy array
indexing dimensions (M, N, P) as in `volume`.
gradient_direction : string
Controls if the mesh was generated from an isosurface with gradient
descent toward objects of interest (the default), or the opposite.
The two options are:
* descent : Object was greater than exterior
* ascent : Exterior was greater than object
'''
verts, faces, normals, values = measure.marching_cubes_lewiner(
volume=voxel,
level=threshold,
spacing=(1., 1., 1.),
gradient_direction='descent')
# Export the mesh as stl
mymesh = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
for i, f in enumerate(faces):
for j in range(3):
mymesh.vectors[i][j] = verts[f[j], :]
file_utils.save_mesh_to_file(imageurl, mymesh)
if __name__ == "__main__":
convertColoredImageToSTL(file.get_image_path())
gray_image[i][j] = get_gray_value_from_color(
pixel_val, distinct_colors)
return gray_image
def get_gray_value_from_color(pixel, distinct_colors):
gray_value = 0
matching_color = color_extractor.get_matching_color(pixel, distinct_colors)
if matching_color is not None:
gray_value = prop.get_height_map()[matching_color] * 0.1
return gray_value
if __name__ == "__main__":
ui.browse_image()
image = cv2.imread(file.get_image_path())
distinct_colors = color_extractor.get_top_colors_hsv(image, 10)
ui.assign_height_to_colors(distinct_colors)
hsv_image = color_converter.get_hsv_from_bgr_image(image)
gray_image = convert_from_colored_to_gray(hsv_image, distinct_colors)
gray_image = cv2.medianBlur(gray_image, 3)
# Perform 'closing' morphological operation on the image
kernel = np.ones((1, 1), np.uint8)
gray_image = cv2.morphologyEx(gray_image, cv2.MORPH_CLOSE, kernel)
# Figure out the scaling parameter according to original size and then scale