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| import pydiffvg | |
| import torch | |
| import skimage | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # Use GPU if available | |
| pydiffvg.set_use_gpu(torch.cuda.is_available()) | |
| canvas_width, canvas_height = 256, 256 | |
| num_control_points = torch.tensor([1]) | |
| points = torch.tensor([[ 50.0, 30.0], # base | |
| [125.0, 400.0], # control point | |
| [170.0, 30.0]]) # base | |
| path = pydiffvg.Path(num_control_points = num_control_points, | |
| points = points, | |
| stroke_width = torch.tensor([30.0]), | |
| is_closed = False, | |
| use_distance_approx = False) | |
| shapes = [path] | |
| path_group = pydiffvg.ShapeGroup(shape_ids = torch.tensor([0]), | |
| fill_color = None, | |
| stroke_color = torch.tensor([0.5, 0.5, 0.5, 0.5])) | |
| shape_groups = [path_group] | |
| scene_args = pydiffvg.RenderFunction.serialize_scene(\ | |
| canvas_width, canvas_height, shapes, shape_groups, | |
| output_type = pydiffvg.OutputType.sdf) | |
| render = pydiffvg.RenderFunction.apply | |
| img = render(256, # width | |
| 256, # height | |
| 1, # num_samples_x | |
| 1, # num_samples_y | |
| 0, # seed | |
| None, # background_image | |
| *scene_args) | |
| img /= 256.0 | |
| cm = plt.get_cmap('viridis') | |
| img = cm(img.squeeze()) | |
| pydiffvg.imwrite(img, 'results/quadratic_distance_approx/ref_sdf.png') | |
| scene_args = pydiffvg.RenderFunction.serialize_scene(\ | |
| canvas_width, canvas_height, shapes, shape_groups) | |
| img = render(256, # width | |
| 256, # height | |
| 2, # num_samples_x | |
| 2, # num_samples_y | |
| 0, # seed | |
| None, # background_image | |
| *scene_args) | |
| pydiffvg.imwrite(img, 'results/quadratic_distance_approx/ref_color.png') | |
| shapes[0].use_distance_approx = True | |
| scene_args = pydiffvg.RenderFunction.serialize_scene(\ | |
| canvas_width, canvas_height, shapes, shape_groups, | |
| output_type = pydiffvg.OutputType.sdf) | |
| img = render(256, # width | |
| 256, # height | |
| 1, # num_samples_x | |
| 1, # num_samples_y | |
| 0, # seed | |
| None, # background_image | |
| *scene_args) | |
| img /= 256.0 | |
| img = cm(img.squeeze()) | |
| pydiffvg.imwrite(img, 'results/quadratic_distance_approx/approx_sdf.png') | |
| scene_args = pydiffvg.RenderFunction.serialize_scene(\ | |
| canvas_width, canvas_height, shapes, shape_groups) | |
| img = render(256, # width | |
| 256, # height | |
| 2, # num_samples_x | |
| 2, # num_samples_y | |
| 0, # seed | |
| None, # background_image | |
| *scene_args) | |
| pydiffvg.imwrite(img, 'results/quadratic_distance_approx/approx_color.png') |