Python nets.mobilenet.mobilenet.mobilenet_base() Examples
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Example #1
Source File: mobilenet_v2_test.py From models with Apache License 2.0 | 6 votes |
def testMultiplier(self): op = mobilenet.op new_def = copy.deepcopy(mobilenet_v2.V2_DEF) def inverse_multiplier(output_params, multiplier): output_params['num_outputs'] = int( output_params['num_outputs'] / multiplier) new_def['spec'][0] = op( slim.conv2d, kernel_size=(3, 3), multiplier_func=inverse_multiplier, num_outputs=16) _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=new_def, depth_multiplier=0.1) s = [op.outputs[0].get_shape().as_list()[-1] for op in find_ops('Conv2D')] # Expect first layer to be 160 (16 / 0.1), and other layers # their max(original size * 0.1, 8) self.assertEqual([160, 8, 48, 8, 48], s[:5])
Example #2
Source File: mobilenet_v2_test.py From MAX-Image-Segmenter with Apache License 2.0 | 5 votes |
def testWithOutputStride8AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, use_explicit_padding=True, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #3
Source File: mobilenet_v2_test.py From models with Apache License 2.0 | 5 votes |
def testWithOutputStride8AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, use_explicit_padding=True, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #4
Source File: mobilenet_v2_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #5
Source File: mobilenet_v2_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #6
Source File: mobilenet_v2_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #7
Source File: mobilenet_v2_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #8
Source File: mobilenet_v2_test.py From models with Apache License 2.0 | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #9
Source File: mobilenet_v2_test.py From models with Apache License 2.0 | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #10
Source File: mobilenet_v2_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def testWithOutputStride16AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16, use_explicit_padding=True) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #11
Source File: mobilenet_v2_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def testWithOutputStride8AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, use_explicit_padding=True, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #12
Source File: mobilenet_v2_test.py From models with Apache License 2.0 | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #13
Source File: mobilenet_v2_test.py From SENet-tensorflow-slim with MIT License | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #14
Source File: mobilenet_v2_test.py From SENet-tensorflow-slim with MIT License | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #15
Source File: mobilenet_v2_test.py From SENet-tensorflow-slim with MIT License | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #16
Source File: mobilenet_v2_test.py From MAX-Image-Segmenter with Apache License 2.0 | 5 votes |
def testWithOutputStride16AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16, use_explicit_padding=True) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #17
Source File: mobilenet_v2_test.py From SENet-tensorflow-slim with MIT License | 5 votes |
def testWithOutputStride16AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16, use_explicit_padding=True) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #18
Source File: mobilenet_v2_test.py From MAX-Image-Segmenter with Apache License 2.0 | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #19
Source File: mobilenet_v2_test.py From MAX-Image-Segmenter with Apache License 2.0 | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #20
Source File: mobilenet_v2_test.py From MAX-Image-Segmenter with Apache License 2.0 | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #21
Source File: mobilenet_v2_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def testWithOutputStride16AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16, use_explicit_padding=True) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #22
Source File: mobilenet_v2_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def testWithOutputStride8AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, use_explicit_padding=True, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #23
Source File: mobilenet_v2_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #24
Source File: mobilenet_v2_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #25
Source File: mobilenet_v2_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #26
Source File: mobilenet_v2_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def testWithOutputStride16AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16, use_explicit_padding=True) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #27
Source File: mobilenet_v2_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def testWithOutputStride8AndExplicitPadding(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, use_explicit_padding=True, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])
Example #28
Source File: mobilenet_v2_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def testWithOutputStride16(self): tf.reset_default_graph() out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=16) self.assertEqual(out.get_shape().as_list()[1:3], [14, 14])
Example #29
Source File: mobilenet_v2_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def testMobilenetBase(self): tf.reset_default_graph() # Verifies that mobilenet_base returns pre-pooling layer. with slim.arg_scope((mobilenet.depth_multiplier,), min_depth=32): net, _ = mobilenet_v2.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, depth_multiplier=0.1) self.assertEqual(net.get_shape().as_list(), [10, 7, 7, 128])
Example #30
Source File: mobilenet_v2_test.py From DeepLab_v3 with MIT License | 5 votes |
def testWithOutputStride8(self): out, _ = mobilenet.mobilenet_base( tf.placeholder(tf.float32, (10, 224, 224, 16)), conv_defs=mobilenet_v2.V2_DEF, output_stride=8, scope='MobilenetV2') self.assertEqual(out.get_shape().as_list()[1:3], [28, 28])