84db7d0ee6
* Build using conanfile.txt * Update .ci/azure/linux_arm64.yml * Several improvements * Removed conanfile.py * Try to use activate / deactivate * Fixed clang-format code style * Supported TBB version from Conan * Added more NOMINMAX * Fixed static build * More improvements for static build * Add usage of static snappy in case of static build * More fixes * Small fixes * Final fixes
107 lines
4.0 KiB
Python
107 lines
4.0 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestNonMaxSuppression(CommonTFLayerTest):
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# overload inputs generation to suit NMS use case
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def _prepare_input(self, inputs_dict):
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channel = ':0' if self.use_old_api or not self.use_new_frontend else ''
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input_data = {}
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for input in inputs_dict.keys():
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input_data[input + channel] = np.random.uniform(low=0, high=1,
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size=inputs_dict[input]).astype(np.float32)
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return input_data
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def create_nms_net(self, test_params: dict, with_scores: bool = False):
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tf.compat.v1.reset_default_graph()
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with tf.compat.v1.Session() as sess:
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# parametrized inputs
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number_of_boxes = test_params["number_of_boxes"]
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max_output_size = tf.constant(test_params["max_output_size"])
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iou_threshold = tf.constant(test_params["iou_threshold"])
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score_threshold = tf.constant(test_params["score_threshold"])
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# inputs to be generated
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boxes = tf.compat.v1.placeholder(tf.float32, [number_of_boxes, 4], "Input")
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# randomize boxes' confidence scores
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np.random.seed(42)
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scores = np.random.uniform(low=0.2, high=1.0, size=[number_of_boxes])
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if with_scores:
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soft_nms_sigma = tf.constant(test_params["soft_nms_sigma"])
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_ = tf.image.non_max_suppression_with_scores(boxes, scores, max_output_size,
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iou_threshold, score_threshold, soft_nms_sigma, name="NMS")
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else:
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_ = tf.image.non_max_suppression(boxes, scores, max_output_size,
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iou_threshold, score_threshold, name="NMS")
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tf_net = sess.graph_def
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ref_net = None
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return tf_net, ref_net
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test_params = [
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(
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{
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"number_of_boxes": 50,
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"max_output_size": 5,
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"iou_threshold": 0.7,
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"score_threshold": 0.8,
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"soft_nms_sigma": 0.1
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}
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),
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(
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{
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"number_of_boxes": 50,
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"max_output_size": 9,
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"iou_threshold": 0.7,
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"score_threshold": 0.7,
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"soft_nms_sigma": 0.4
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}
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),
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(
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{
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"number_of_boxes": 50,
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"max_output_size": 3,
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"iou_threshold": 0.3,
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"score_threshold": 0.8,
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"soft_nms_sigma": 0.7
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}
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)
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]
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@pytest.mark.parametrize("test_params", test_params)
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_tf_fe
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def test_NonMaxSuppression(self, test_params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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if ie_device == 'GPU':
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pytest.skip("Skip TF NonMaxSuppresion test on GPU")
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self.use_old_api = use_old_api
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self._test(*self.create_nms_net(test_params), ie_device, precision,
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ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend,
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use_old_api=use_old_api)
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@pytest.mark.parametrize("test_params", test_params)
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@pytest.mark.nightly
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@pytest.mark.precommit
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@pytest.mark.precommit_tf_fe
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def test_NonMaxSuppressionWithScores(self, test_params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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if ie_device == 'GPU':
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pytest.skip("Skip TF NonMaxSuppresionWithScores test on GPU")
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self.use_old_api = use_old_api
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self._test(*self.create_nms_net(test_params, with_scores=True), ie_device, precision,
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ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend,
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use_old_api=use_old_api)
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