| /external/ImageMagick/MagickCore/ |
| D | list.c | 77 MagickExport void AppendImageToList(Image **images,const Image *append) in AppendImageToList() argument
83 assert(images != (Image **) NULL); in AppendImageToList()
89 if ((*images) == (Image *) NULL) in AppendImageToList()
91 *images=(Image *) append; in AppendImageToList()
94 assert((*images)->signature == MagickCoreSignature); in AppendImageToList()
95 p=GetLastImageInList(*images); in AppendImageToList()
125 MagickExport Image *CloneImageList(const Image *images,ExceptionInfo *exception) in CloneImageList() argument
134 if (images == (Image *) NULL) in CloneImageList()
136 assert(images->signature == MagickCoreSignature); in CloneImageList()
137 while (images->previous != (Image *) NULL) in CloneImageList()
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| /external/ImageMagick/PerlMagick/demo/ |
| D | demo.pl | 31 $images=Image::Magick->new();
37 push(@$images,$example);
43 push(@$images,$example);
49 push(@$images,$example);
55 push(@$images,$example);
61 push(@$images,$example);
68 push(@$images,$example);
74 push(@$images,$example);
80 push(@$images,$example);
86 push(@$images,$example);
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| /external/ImageMagick/www/source/ |
| D | examples.pl | 31 $images=Image::Magick->new();
37 push(@$images,$example);
43 push(@$images,$example);
49 push(@$images,$example);
55 push(@$images,$example);
61 push(@$images,$example);
68 push(@$images,$example);
74 push(@$images,$example);
80 push(@$images,$example);
86 push(@$images,$example);
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| /external/ImageMagick/Magick++/demo/ |
| D | demo.cpp | 63 list<Image> images( 7, null ); in main() local
76 images.push_back( example ); in main()
81 images.push_back( example ); in main()
92 images.push_back( example ); in main()
98 images.push_back( example ); in main()
104 images.push_back( example ); in main()
111 images.push_back( example ); in main()
117 images.push_back( example ); in main()
123 images.push_back( example ); in main()
129 images.push_back( example ); in main()
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| /external/ImageMagick/MagickWand/ |
| D | magick-image.c | 88 Image *images) in CloneMagickWandFromImages() argument
100 images->filename); in CloneMagickWandFromImages()
108 clone_wand->images=images; in CloneMagickWandFromImages()
144 if (wand->images == (Image *) NULL) in GetImageFromMagickWand()
150 return(wand->images); in GetImageFromMagickWand()
196 if (wand->images == (Image *) NULL) in MagickAdaptiveBlurImage()
198 sharp_image=AdaptiveBlurImage(wand->images,radius,sigma,wand->exception); in MagickAdaptiveBlurImage()
201 ReplaceImageInList(&wand->images,sharp_image); in MagickAdaptiveBlurImage()
241 if (wand->images == (Image *) NULL) in MagickAdaptiveResizeImage()
243 resize_image=AdaptiveResizeImage(wand->images,columns,rows,wand->exception); in MagickAdaptiveResizeImage()
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| D | magick-wand.c | 84 wand->images=DestroyImageList(wand->images); in ClearMagickWand()
134 clone_wand->images=CloneImageList(wand->images,clone_wand->exception); in CloneMagickWand()
172 wand->images=DestroyImageList(wand->images); in DestroyMagickWand()
368 if (wand->images == (Image *) NULL) in MagickGetIteratorIndex()
374 return(GetImageIndexInList(wand->images)); in MagickGetIteratorIndex()
532 if (wand->images == (Image *) NULL) in MagickQueryFontMetrics()
549 status=GetTypeMetrics(wand->images,draw_info,&metrics,wand->exception); in MagickQueryFontMetrics()
639 if (wand->images == (Image *) NULL) in MagickQueryMultilineFontMetrics()
656 status=GetMultilineTypeMetrics(wand->images,draw_info,&metrics, in MagickQueryMultilineFontMetrics()
829 wand->images=GetFirstImageInList(wand->images); in MagickResetIterator()
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| /external/tensorflow/tensorflow/python/layers/ |
| D | pooling_test.py | 31 images = random_ops.random_uniform((5, height, width, 3), seed=1)
33 pooling_layers.max_pooling2d(images, 3, strides=2, data_format='invalid')
37 images = random_ops.random_uniform((5, height, width, 3), seed=1)
39 pooling_layers.max_pooling2d(images, 3, strides=(1, 2, 3))
42 pooling_layers.max_pooling2d(images, 3, strides=None)
46 images = random_ops.random_uniform((5, height, width, 3), seed=1)
48 pooling_layers.max_pooling2d(images, (1, 2, 3), strides=2)
51 pooling_layers.max_pooling2d(images, None, strides=2)
55 images = random_ops.random_uniform((5, height, width, 4))
57 output = layer.apply(images)
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| D | convolutional_test.py | 42 images = random_ops.random_uniform((5, height, width, 3), seed=1)
44 conv_layers.conv2d(images, 32, 3, data_format='invalid')
48 images = random_ops.random_uniform((5, height, width, 3), seed=1)
50 conv_layers.conv2d(images, 32, 3, strides=(1, 2, 3))
53 conv_layers.conv2d(images, 32, 3, strides=None)
57 images = random_ops.random_uniform((5, height, width, 3), seed=1)
59 conv_layers.conv2d(images, 32, (1, 2, 3))
62 conv_layers.conv2d(images, 32, None)
66 images = random_ops.random_uniform((5, height, width, 4))
68 output = layer.apply(images)
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| /external/wayland/cursor/ |
| D | wayland-cursor.c | 195 wl_cursor_image_destroy(cursor->images[i]); in wl_cursor_destroy()
197 free(cursor->images); in wl_cursor_destroy()
217 cursor->cursor.images = malloc(sizeof *cursor->cursor.images); in wl_cursor_create_from_data()
218 if (!cursor->cursor.images) in wl_cursor_create_from_data()
228 cursor->cursor.images[0] = (struct wl_cursor_image *) image; in wl_cursor_create_from_data()
253 free(cursor->cursor.images); in wl_cursor_create_from_data()
287 wl_cursor_create_from_xcursor_images(XcursorImages *images, in wl_cursor_create_from_xcursor_images() argument
298 cursor->cursor.images = in wl_cursor_create_from_xcursor_images()
299 malloc(images->nimage * sizeof cursor->cursor.images[0]); in wl_cursor_create_from_xcursor_images()
300 if (!cursor->cursor.images) { in wl_cursor_create_from_xcursor_images()
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| D | xcursor.c | 227 XcursorImages *images; in XcursorImagesCreate() local
229 images = malloc (sizeof (XcursorImages) + in XcursorImagesCreate()
231 if (!images) in XcursorImagesCreate()
233 images->nimage = 0; in XcursorImagesCreate()
234 images->images = (XcursorImage **) (images + 1); in XcursorImagesCreate()
235 images->name = NULL; in XcursorImagesCreate()
236 return images; in XcursorImagesCreate()
240 XcursorImagesDestroy (XcursorImages *images) in XcursorImagesDestroy() argument
244 if (!images) in XcursorImagesDestroy()
247 for (n = 0; n < images->nimage; n++) in XcursorImagesDestroy()
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | layers_test.py | 60 images = np.random.uniform(size=(5, height, width, 3))
63 _layers.avg_pool2d(images, [3, 3], data_format='CHWN')
67 images = np.random.uniform(size=(5, height, width, 3))
68 output = _layers.avg_pool2d(images, [3, 3])
74 images = np.random.uniform(size=(5, 2, height, width))
75 output = _layers.avg_pool2d(images, [3, 3], data_format='NCHW')
80 images = random_ops.random_uniform((5, height, width, 3), seed=1)
81 output = _layers.avg_pool2d(images, [3, 3], outputs_collections='outputs')
88 images = random_ops.random_uniform((5, height, width, 3), seed=1)
89 output = _layers.avg_pool2d(images, 3)
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| D | normalization_test.py | 57 images = random_ops.random_uniform((5, height, width, 3), seed=1)
58 output = normalization.instance_norm(images)
66 images = random_ops.random_uniform(
68 output = normalization.instance_norm(images)
75 images = random_ops.random_uniform(
77 output = normalization.instance_norm(images, center=False, scale=False)
86 images = random_ops.random_uniform((5, height, width, 3), seed=1)
87 normalization.instance_norm(images, center=True, scale=True)
95 images = random_ops.random_uniform((5, height, width, 3), seed=1)
96 normalization.instance_norm(images, scale=True, scope='IN')
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| /external/tensorflow/tensorflow/python/ops/ |
| D | image_ops_impl.py | 432 def _rot90_4D(images, k, name_scope): argument
446 return array_ops.transpose(array_ops.reverse_v2(images, [2]),
449 return array_ops.reverse_v2(images, [1, 2])
451 return array_ops.reverse_v2(array_ops.transpose(images, [0, 2, 1, 3]),
458 result = control_flow_ops.case(cases, default=lambda: images, exclusive=True,
837 def resize_images(images, argument
885 with ops.name_scope(None, 'resize_images', [images, size]):
886 images = ops.convert_to_tensor(images, name='images')
887 if images.get_shape().ndims is None:
891 if images.get_shape().ndims == 3:
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| /external/autotest/client/cros/chameleon/ |
| D | screen_comparison.py | 55 images = [self._capturer1.capture(), self._capturer2.capture()]
57 if None in images:
59 tags[images.index(None)])
66 for i, image in enumerate(images):
68 images[i] = image.convert('RGB')
74 if images[0].size != images[1].size:
77 (tuple(tags) + images[0].size + images[1].size))
85 size = images[0].size[0] * images[0].size[1]
89 diff_image = ImageChops.difference(*images)
97 prefix_str = '%s-%dx%d' % ((time_str,) + images[0].size)
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| /external/tensorflow/tensorflow/contrib/image/python/ops/ |
| D | image_ops.py | 42 def rotate(images, angles, interpolation="NEAREST", name=None): argument
63 image_or_images = ops.convert_to_tensor(images)
69 images = image_or_images[None, :, :, None]
71 images = image_or_images[None, :, :, :]
73 images = image_or_images
77 image_height = math_ops.cast(array_ops.shape(images)[1],
79 image_width = math_ops.cast(array_ops.shape(images)[2],
82 images,
95 def translate(images, translations, interpolation="NEAREST", name=None): argument
118 images,
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| D | resnet50_test.py | 46 images = tf.random_uniform(shape)
51 return images, one_hot
54 def train_one_step(model, images, labels, optimizer): argument
57 logits = model(images, training=True)
73 images, _ = random_batch(2)
74 output = model(images)
87 images, _ = random_batch(2)
88 output = model(images)
97 images, _ = random_batch(2)
98 output = model(images)
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| D | resnet50_graph_test.py | 42 images = np.random.rand(*image_shape(batch_size)).astype(np.float32)
48 return images, one_hot
56 images = tf.placeholder(tf.float32, image_shape(None))
58 predictions = model(images)
65 out = sess.run(predictions, feed_dict={images: np_images})
70 images = tf.placeholder(tf.float32, image_shape(None), name='images')
80 logits = model(images, training=True)
96 feed_dict={images: np_images, labels: np_labels})
115 images = tf.placeholder(tf.float32, image_shape(None))
117 predictions = model(images)
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| /external/tensorflow/tensorflow/contrib/receptive_field/python/util/examples/ |
| D | rf_benchmark.py | 98 images = array_ops.placeholder(
103 _, end_points = inception.inception_resnet_v2_base(images)
106 images, align_feature_maps=True)
108 _, end_points = inception.inception_v2_base(images)
111 images, use_separable_conv=False)
113 _, end_points = inception.inception_v3_base(images)
115 _, end_points = inception.inception_v4_base(images)
117 _, end_points = alexnet.alexnet_v2(images)
119 _, end_points = vgg.vgg_a(images)
121 _, end_points = vgg.vgg_16(images)
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| /external/wayland/doc/publican/ |
| D | Makefile.am | 28 $(srcdir)/sources/images/icon.svg \
29 $(srcdir)/sources/images/wayland.png \
45 $(srcdir)/sources/images/icon.svg \
46 $(srcdir)/sources/images/wayland.png
66 …dirs := $(builddir)/en-US $(builddir)/en-US/images $(html_destdir) $(html_destdir)/css $(html_dest…
70 html_img_targets = $(addprefix $(html_destdir)/images/,$(notdir $(img_sources)))
71 doxygen_img_targets := $(doxygen_img_sources:$(doxydir)/xml/%=$(html_destdir)/images/%)
72 map_targets := $(map_sources:$(doxydir)/xml/%=$(builddir)/en-US/images/%)
82 $(html_destdir)/images/%: $(srcdir)/sources/images/% | $(html_destdir)/images
85 $(html_destdir)/images/%: $(doxydir)/xml/% | $(html_destdir)/images
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| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| D | classifier_metrics_impl.py | 77 def _validate_images(images, image_size): argument
78 images = ops.convert_to_tensor(images)
79 images.shape.with_rank(4)
80 images.shape.assert_is_compatible_with(
82 return images
113 images, height=INCEPTION_DEFAULT_IMAGE_SIZE, argument
132 is_single = images.shape.ndims == 3
133 with ops.name_scope(scope, 'preprocess', [images, height, width]):
134 if not images.dtype.is_floating:
135 images = math_ops.to_float(images)
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| D | eval_utils_impl.py | 83 def _validate_images(images): argument
84 for img in images:
92 def image_reshaper(images, num_cols=None): argument
112 if isinstance(images, ops.Tensor):
113 images = array_ops.unstack(images)
114 _validate_images(images)
116 num_images = len(images)
120 rows = [images[x:x+num_columns] for x in range(0, num_images, num_columns)]
126 rows[-1].extend([array_ops.zeros_like(images[-1])] * num_short)
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/datasets/ |
| D | mnist.py | 108 images, argument
131 assert images.shape[0] == labels.shape[0], (
132 'images.shape: %s labels.shape: %s' % (images.shape, labels.shape))
133 self._num_examples = images.shape[0]
138 assert images.shape[3] == 1
139 images = images.reshape(images.shape[0],
140 images.shape[1] * images.shape[2])
143 images = images.astype(numpy.float32)
144 images = numpy.multiply(images, 1.0 / 255.0)
145 self._images = images
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| /external/libxml2/doc/ |
| D | Makefile.am | 23 $(wildcard tutorial/images/*.png) \
24 $(wildcard tutorial/images/callouts/*.png) $(wildcard API*.html) \
190 tutorial/images/blank.png \
191 tutorial/images/callouts/1.png \
192 tutorial/images/callouts/10.png \
193 tutorial/images/callouts/2.png \
194 tutorial/images/callouts/3.png \
195 tutorial/images/callouts/4.png \
196 tutorial/images/callouts/5.png \
197 tutorial/images/callouts/6.png \
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| /external/tensorflow/tensorflow/docs_src/api_guides/python/ |
| D | image.md | 11 images are represented by scalar string Tensors, decoded images by 3-D uint8
15 are all of variable size. If you need fixed size images, pass the output of
32 The resizing Ops accept input images as tensors of several types. They always
33 output resized images as float32 tensors.
36 and 3-D tensors as input and output. 4-D tensors are for batches of images,
37 3-D tensors for individual images.
39 Other resizing Ops only support 4-D batches of images as input:
78 Image ops work either on individual images or on batches of images, depending on
83 Tensor represents `batch_size` images.
85 Currently, `channels` can usefully be 1, 2, 3, or 4. Single-channel images are
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| /external/vulkan-validation-layers/tests/ |
| D | README-raster_tests | 3 …images generated from previous runs. To generate golden images, make sure that the tests are rend…
5 …images to the golden images, run with --compare-images. This too will generate .ppm images for al…
|