initial commit

apps/quadratic_distance_approx.py

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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')