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Merge pull request #5 from oeway/fix-background_image

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Fix missing background_image argument
This commit is contained in:
Tzu-Mao Li
2020-09-30 10:38:27 -04:00
committed by GitHub
parent 0c596d3b57 08739cdd0a
commit 2ec688ebb7
17 changed files with 67 additions and 6 deletions
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4
apps/single_curve_outline.py
View File

@@ -34,6 +34,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_curve_outline/target.png', gamma=2.2)
@@ -65,6 +66,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_curve_outline/init.png', gamma=2.2)
@@ -86,6 +88,7 @@ for t in range(200):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_curve_outline/iter_{}.png'.format(t), gamma=2.2)
@@ -121,6 +124,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
202, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_curve_outline/final.png')

4
apps/single_curve_sdf.py
View File

@@ -34,6 +34,7 @@ img = render(256, # width
1, # num_samples_x
1, # num_samples_y
0, # seed
None, # background_image
*scene_args)
img /= 256.0
# The output image is in linear RGB space. Do Gamma correction before saving the image.
@@ -63,6 +64,7 @@ img = render(256, # width
1, # num_samples_x
1, # num_samples_y
1, # seed
None, # background_image
*scene_args)
img /= 256.0
pydiffvg.imwrite(img.cpu(), 'results/single_curve_sdf/init.png', gamma=1.0)
@@ -84,6 +86,7 @@ for t in range(100):
1, # num_samples_x
1, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
img /= 256.0
# Save the intermediate render.
@@ -113,6 +116,7 @@ img = render(256, # width
1, # num_samples_x
1, # num_samples_y
102, # seed
None, # background_image
*scene_args)
img /= 256.0
# Save the images and differences.

6
apps/single_curve_sdf_trans.py
View File

@@ -40,6 +40,7 @@ img = render(256, # width
1, # num_samples_x
1, # num_samples_y
0, # seed
None, # background_image
*scene_args)
path.points[:, 1] += 1e-3
@@ -51,6 +52,7 @@ img2 = render(256, # width
1, # num_samples_x
1, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# diff = img2 - img
@@ -70,6 +72,7 @@ img = render_grad(torch.ones(256, 256, 1), # grad_img
1, # num_samples_x
1, # num_samples_y
0, # seed
None, # background_image
*scene_args)
img = img[:, :, 0]
import matplotlib.pyplot as plt
@@ -109,6 +112,7 @@ plt.show()
# 1, # num_samples_x
# 1, # num_samples_y
# 1, # seed
# None, # background_image
# *scene_args)
# img /= 256.0
# pydiffvg.imwrite(img.cpu(), 'results/single_curve_sdf/init.png', gamma=1.0)
@@ -130,6 +134,7 @@ plt.show()
# 1, # num_samples_x
# 1, # num_samples_y
# t+1, # seed
# None, # background_image
# *scene_args)
# img /= 256.0
# # Save the intermediate render.
@@ -160,6 +165,7 @@ plt.show()
# 1, # num_samples_x
# 1, # num_samples_y
# 102, # seed
# None, # background_image
# *scene_args)
# img /= 256.0
# # Save the images and differences.

4
apps/single_ellipse.py
View File

@@ -22,6 +22,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse/target.png', gamma=2.2)
@@ -42,6 +43,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse/init.png', gamma=2.2)
@@ -62,6 +64,7 @@ for t in range(50):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse/iter_{}.png'.format(t), gamma=2.2)
@@ -94,6 +97,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
52, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse/final.png')

4
apps/single_ellipse_transform.py
View File

@@ -24,6 +24,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse_transform/target.png', gamma=2.2)
@@ -49,6 +50,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse_transform/init.png', gamma=2.2)
@@ -68,6 +70,7 @@ for t in range(150):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse_transform/iter_{}.png'.format(t), gamma=2.2)
@@ -97,6 +100,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
52, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_ellipse_transform/final.png')

4
apps/single_gradient.py
View File

@@ -27,6 +27,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_gradient/target.png', gamma=2.2)
@@ -54,6 +55,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_gradient/init.png', gamma=2.2)
@@ -77,6 +79,7 @@ for t in range(100):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_gradient/iter_{}.png'.format(t), gamma=2.2)
@@ -116,6 +119,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
52, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_gradient/final.png')

5
apps/single_open_curve.py
View File

@@ -13,7 +13,6 @@ points = torch.tensor([[120.0, 30.0], # base
[ 60.0, 218.0]]) # base
path = pydiffvg.Path(num_control_points = num_control_points,
points = points,
thickness = None,
is_closed = False,
stroke_width = torch.tensor(5.0))
shapes = [path]
@@ -30,6 +29,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve/target.png', gamma=2.2)
@@ -54,6 +54,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve/init.png', gamma=2.2)
@@ -74,6 +75,7 @@ for t in range(200):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve/iter_{}.png'.format(t), gamma=2.2)
@@ -106,6 +108,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
202, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve/final.png')

4
apps/single_open_curve_thickness.py
View File

@@ -32,6 +32,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve_thickness/target.png', gamma=2.2)
@@ -57,6 +58,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve_thickness/init.png', gamma=2.2)
@@ -77,6 +79,7 @@ for t in range(200):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve_thickness/iter_{}.png'.format(t), gamma=2.2)
@@ -109,6 +112,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
202, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_open_curve_thickness/final.png')

4
apps/single_path.py
View File

@@ -20,6 +20,7 @@ img = render(510, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_path/target.png', gamma=2.2)
@@ -40,6 +41,7 @@ img = render(510, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_path/init.png', gamma=2.2)
@@ -59,6 +61,7 @@ for t in range(100):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_path/iter_{:02}.png'.format(t), gamma=2.2)
@@ -88,6 +91,7 @@ img = render(510, # width
2, # num_samples_x
2, # num_samples_y
102, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_path/final.png')

4
apps/single_path_sdf.py
View File

@@ -21,6 +21,7 @@ img = render(510, # width
1, # num_samples_x
1, # num_samples_y
0, # seed
None, # background_image
*scene_args)
img = img / 510 # Normalize SDF to [0, 1]
pydiffvg.imwrite(img.cpu(), 'results/single_path_sdf/target.png', gamma=1.0)
@@ -42,6 +43,7 @@ img = render(510, # width
1, # num_samples_x
1, # num_samples_y
1, # seed
None, # background_image
*scene_args)
img = img / 510 # Normalize SDF to [0, 1]
pydiffvg.imwrite(img.cpu(), 'results/single_path_sdf/init.png', gamma=1.0)
@@ -63,6 +65,7 @@ for t in range(100):
1, # num_samples_x
1, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
img = img / 510 # Normalize SDF to [0, 1]
# Save the intermediate render.
@@ -94,6 +97,7 @@ img = render(510, # width
1, # num_samples_x
1, # num_samples_y
102, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_path_sdf/final.png')

4
apps/single_polygon.py
View File

@@ -27,6 +27,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_polygon/target.png', gamma=2.2)
@@ -49,6 +50,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_polygon/init.png', gamma=2.2)
@@ -68,6 +70,7 @@ for t in range(100):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_polygon/iter_{}.png'.format(t), gamma=2.2)
@@ -97,6 +100,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
102, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_polygon/final.png')

4
apps/single_rect.py
View File

@@ -22,6 +22,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_rect/target.png', gamma=2.2)
@@ -42,6 +43,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_rect/init.png', gamma=2.2)
@@ -62,6 +64,7 @@ for t in range(100):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_rect/iter_{}.png'.format(t), gamma=2.2)
@@ -91,6 +94,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
102, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_rect/final.png')

4
apps/single_stroke.py
View File

@@ -30,6 +30,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'results/single_stroke/target.png', gamma=2.2)
@@ -54,6 +55,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
pydiffvg.imwrite(img.cpu(), 'results/single_stroke/init.png', gamma=2.2)
@@ -74,6 +76,7 @@ for t in range(200):
2, # num_samples_x
2, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
# Save the intermediate render.
pydiffvg.imwrite(img.cpu(), 'results/single_stroke/iter_{}.png'.format(t), gamma=2.2)
@@ -106,6 +109,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
202, # seed
None, # background_image
*scene_args)
# Save the images and differences.
pydiffvg.imwrite(img.cpu(), 'results/single_stroke/final.png')

8
apps/svg_parse_test.py
View File

@@ -21,9 +21,9 @@ for x in range(100000):
print(outmat)
print(decomp)"""
#infile='../../data/test_data/linear_grad_alpha_aspaths.svg'
#infile='../../data/note_small.svg'
infile='linux.svg'
infile='./imgs/note_small.svg'
canvas_width, canvas_height, shapes, shape_groups = \
pydiffvg.svg_to_scene(infile)
@@ -35,6 +35,7 @@ img = render(canvas_width, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
# The output image is in linear RGB space. Do Gamma correction before saving the image.
pydiffvg.imwrite(img.cpu(), 'test_old.png', gamma=1.0)
@@ -50,6 +51,7 @@ img = render(scene[0], # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)

6
apps/test_eval_positions.py
View File

@@ -24,6 +24,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
0, # seed
None, # background_image
*scene_args)
img = img / 256 # Normalize SDF to [0, 1]
pydiffvg.imwrite(img.cpu(), 'results/test_eval_positions/target.png')
@@ -45,6 +46,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
1, # seed
None, # background_image
*scene_args)
img = img / 256 # Normalize SDF to [0, 1]
pydiffvg.imwrite(img.cpu(), 'results/test_eval_positions/init.png')
@@ -60,7 +62,7 @@ for t in range(200):
circle.center = center_n * 256
circle_group.fill_color = color
# Evaluate 1000 positions
eval_positions = torch.rand(1000, 2) * 256
eval_positions = torch.rand(1000, 2).to(img.device) * 256
# for grid_sample()
grid_eval_positions = (eval_positions / 256.0) * 2.0 - 1.0
scene_args = pydiffvg.RenderFunction.serialize_scene(\
@@ -72,6 +74,7 @@ for t in range(200):
0, # num_samples_x
0, # num_samples_y
t+1, # seed
None, # background_image
*scene_args)
samples = samples / 256 # Normalize SDF to [0, 1]
target_sampled = torch.nn.functional.grid_sample(\
@@ -103,6 +106,7 @@ img = render(256, # width
2, # num_samples_x
2, # num_samples_y
102, # seed
None, # background_image
*scene_args)
img = img / 256 # Normalize SDF to [0, 1]
# Save the images and differences.

1
pydiffvg/optimize_svg.py
View File

@@ -1028,6 +1028,7 @@ class OptimizableSvg:
2, # num_samples_x
2, # num_samples_y
seed, # seed
None, # background_image
*scene_args)
return img

3
pydiffvg_tensorflow/render_tensorflow.py
View File

@@ -1,3 +1,4 @@
import os
import tensorflow as tf
import diffvg
import pydiffvg_tensorflow as pydiffvg
@@ -457,7 +458,7 @@ def render(*x):
The main TensorFlow interface of C++ diffvg.
"""
assert(tf.executing_eagerly())
if pydiffvg.get_use_gpu() and os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] != 'true':
if pydiffvg.get_use_gpu() and os.environ.get('TF_FORCE_GPU_ALLOW_GROWTH') != 'true':
print('******************** WARNING ********************')
print('Tensorflow by default allocates all GPU memory,')
print('causing huge amount of page faults when rendering.')