Added support for attribute 'pad_to_max_dimension' for TF OD API models (#4720)
* Added support for attribute 'pad_to_max_dimension' for TF OD API models * Restored line removed by mistake
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Evgeny Lazarev authored and 
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@@ -363,7 +363,8 @@ def skip_nodes_by_condition(current_node: Node, condition: callable):
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return current_node
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def calculate_shape_keeping_aspect_ratio(height: int, width: int, min_size: int, max_size: int):
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def calculate_shape_keeping_aspect_ratio(height: int, width: int, min_size: int, max_size: int,
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pad_to_max_dimension: bool = False):
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"""
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The function scales spatial sizes of the image keeping aspect ratio to satisfy provided requirements.
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The behavior of this function is equivalent to the output shape calculation of the Preprocessor block of TensorFlow
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@@ -372,8 +373,11 @@ def calculate_shape_keeping_aspect_ratio(height: int, width: int, min_size: int,
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:param width: input width.
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:param min_size: size limit.
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:param max_size: size limit.
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:param pad_to_max_dimension: scale the input image size to the maximum value specified
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:return: the tuple with scaled image height, width.
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"""
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if pad_to_max_dimension:
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return max_size, max_size
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ratio_min = min_size / min(height, width)
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ratio_max = max_size / max(height, width)
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ratio = min(ratio_min, ratio_max)
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@@ -441,6 +445,7 @@ def calculate_placeholder_spatial_shape(graph: Graph, match: SubgraphMatch, pipe
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# if the model is created with an input image resizer keeping aspect ratio
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if resizer_min_dimension and resizer_max_dimension:
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pad_to_max_dimension = pipeline_config.get_param('pad_to_max_dimension')
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print('[ WARNING ] Model Optimizer removes pre-processing block of the model which resizes image keeping '
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'aspect ratio. The Inference Engine does not support dynamic image size so the Intermediate '
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'Representation file is generated with the input image size of a fixed size.')
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@@ -448,7 +453,8 @@ def calculate_placeholder_spatial_shape(graph: Graph, match: SubgraphMatch, pipe
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scaled_height, scaled_width = calculate_shape_keeping_aspect_ratio(user_defined_height,
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user_defined_width,
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resizer_min_dimension,
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resizer_max_dimension)
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resizer_max_dimension,
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pad_to_max_dimension)
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if scaled_height != user_defined_height or scaled_width != user_defined_width:
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log.error('The model resizes the input image keeping aspect ratio with min dimension {}, max '
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'dimension {}. The provided input height {}, width {} is transformed to height {}, width '
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@@ -457,7 +463,10 @@ def calculate_placeholder_spatial_shape(graph: Graph, match: SubgraphMatch, pipe
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height = scaled_height
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width = scaled_width
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else:
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height = width = resizer_min_dimension
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if pad_to_max_dimension:
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height = width = resizer_max_dimension
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else:
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height = width = resizer_min_dimension
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print('Specify the "--input_shape" command line parameter to override the default shape which is equal to '
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'({}, {}).'.format(height, width))
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@@ -16,6 +16,8 @@
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import unittest
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from generator import generator, generate
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from extensions.front.tf.ObjectDetectionAPI import calculate_shape_keeping_aspect_ratio, \
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calculate_placeholder_spatial_shape
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from mo.front.subgraph_matcher import SubgraphMatch
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@@ -34,58 +36,33 @@ class FakePipelineConfig:
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return self._model_params[param]
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@generator
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class TestCalculateShape(unittest.TestCase):
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min_size = 600
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max_size = 1024
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def test_calculate_shape_1(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(100, 300, self.min_size, self.max_size), (341, 1024))
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def test_calculate_shape_2(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(100, 600, self.min_size, self.max_size), (171, 1024))
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def test_calculate_shape_3(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(100, 3000, self.min_size, self.max_size), (34, 1024))
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def test_calculate_shape_4(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(300, 300, self.min_size, self.max_size), (600, 600))
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def test_calculate_shape_5(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(300, 400, self.min_size, self.max_size), (600, 800))
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def test_calculate_shape_6(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(300, 600, self.min_size, self.max_size), (512, 1024))
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def test_calculate_shape_7(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(1000, 2500, self.min_size, self.max_size),
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(410, 1024))
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def test_calculate_shape_8(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(1800, 2000, self.min_size, self.max_size),
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(600, 667))
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def test_calculate_shape_11(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(300, 100, self.min_size, self.max_size), (1024, 341))
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def test_calculate_shape_12(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(600, 100, self.min_size, self.max_size), (1024, 171))
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def test_calculate_shape_13(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(3000, 100, self.min_size, self.max_size), (1024, 34))
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def test_calculate_shape_15(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(400, 300, self.min_size, self.max_size), (800, 600))
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def test_calculate_shape_16(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(600, 300, self.min_size, self.max_size), (1024, 512))
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def test_calculate_shape_17(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(2500, 1000, self.min_size, self.max_size),
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(1024, 410))
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def test_calculate_shape_18(self):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(2000, 1800, self.min_size, self.max_size),
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(667, 600))
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@generate(*[(100, 300, 341, 1024, False),
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(100, 600, 171, 1024, False),
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(100, 3000, 34, 1024, False),
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(300, 300, 600, 600, False),
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(300, 400, 600, 800, False),
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(300, 600, 512, 1024, False),
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(1000, 2500, 410, 1024, False),
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(1800, 2000, 600, 667, False),
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(300, 100, 1024, 341, False),
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(600, 100, 1024, 171, False),
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(3000, 100, 1024, 34, False),
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(400, 300, 800, 600, False),
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(600, 300, 1024, 512, False),
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(2500, 1000, 1024, 410, False),
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(2000, 1800, 667, 600, False),
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(300, 300, 1024, 1024, True),
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(900, 300, 1024, 1024, True),
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(1300, 900, 1024, 1024, True),
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(1025, 1025, 1024, 1024, True),
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])
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def test_calculate_shape(self, h, w, th, tw, pad):
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self.assertTupleEqual(calculate_shape_keeping_aspect_ratio(h, w, self.min_size, self.max_size, pad), (th, tw))
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class TestCalculatePlaceholderSpatialShape(unittest.TestCase):
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@@ -122,5 +99,13 @@ class TestCalculatePlaceholderSpatialShape(unittest.TestCase):
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self.assertTupleEqual((800, 600),
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calculate_placeholder_spatial_shape(self.graph, self.match, self.pipeline_config))
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def test_keep_aspect_ratio_resizer_overrided_by_user_pad(self):
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self.pipeline_config._model_params['resizer_min_dimension'] = 600
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self.pipeline_config._model_params['resizer_max_dimension'] = 1024
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self.pipeline_config._model_params['pad_to_max_dimension'] = True
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self.graph.graph['user_shapes'] = {'image_tensor': [{'shape': [1, 400, 300, 3]}]}
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self.assertTupleEqual((1024, 1024),
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calculate_placeholder_spatial_shape(self.graph, self.match, self.pipeline_config))
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def test_missing_input_shape_information(self):
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self.assertRaises(Error, calculate_placeholder_spatial_shape, self.graph, self.match, self.pipeline_config)
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@@ -32,6 +32,7 @@ mapping_rules = [
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('resizer_image_width', 'image_resizer/fixed_shape_resizer/width'),
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('resizer_min_dimension', 'image_resizer/keep_aspect_ratio_resizer/min_dimension'),
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('resizer_max_dimension', 'image_resizer/keep_aspect_ratio_resizer/max_dimension'),
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('pad_to_max_dimension', 'image_resizer/keep_aspect_ratio_resizer/pad_to_max_dimension', False),
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# anchor generator attributes
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('anchor_generator_height', 'first_stage_anchor_generator/grid_anchor_generator/height$', 256),
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('anchor_generator_width', 'first_stage_anchor_generator/grid_anchor_generator/width$', 256),
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@@ -151,6 +151,7 @@ class TestingSimpleProtoParser(unittest.TestCase):
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'use_matmul_crop_and_resize': False,
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'add_background_class': True,
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'share_box_across_classes': False,
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'pad_to_max_dimension': False,
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}
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os.unlink(file_name)
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self.assertDictEqual(pipeline_config._model_params, expected_result)
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