# Copyright (c) OpenMMLab. All rights reserved. import os.path as osp import numpy as np import pytest from numpy.testing import assert_array_almost_equal, assert_array_equal from mmaction.models.localizers.utils import (generate_bsp_feature, generate_candidate_proposals, soft_nms, temporal_iop, temporal_iou) def test_temporal_iou(): anchors_min = np.array([0.0, 0.5]) anchors_max = np.array([1.0, 1.5]) box_min = 0.5 box_max = 1.0 iou = temporal_iou(anchors_min, anchors_max, box_min, box_max) assert_array_equal(iou, np.array([0.5, 0.5])) def test_temporal_iop(): anchors_min = np.array([0.0, 0.5]) anchors_max = np.array([1.0, 1.5]) box_min = 0.4 box_max = 1.1 ioa = temporal_iop(anchors_min, anchors_max, box_min, box_max) assert_array_almost_equal(ioa, np.array([0.6, 0.6])) def test_soft_nms(): proposals = np.array([[0., 1., 1., 1., 0.5, 0.5], [0., 0.4, 1., 1., 0.4, 0.4], [0., 0.95, 1., 1., 0.6, 0.6]]) proposal_list = soft_nms(proposals, 0.75, 0.65, 0.9, 1) assert_array_equal(proposal_list, [[0., 0.95, 0.6], [0., 0.4, 0.4]]) def test_generate_candidate_proposals(): video_list = [0, 1] video_infos = [ dict( video_name='v_test1', duration_second=100, duration_frame=1000, annotations=[{ 'segment': [30.0, 60.0], 'label': 'Rock climbing' }], feature_frame=900), dict( video_name='v_test2', duration_second=100, duration_frame=1000, annotations=[{ 'segment': [6.0, 8.0], 'label': 'Drinking beer' }], feature_frame=900) ] tem_results_dir = osp.normpath( osp.join(osp.dirname(__file__), '../../data/tem_results')) # test when tem_result_ext is not valid with pytest.raises(NotImplementedError): result_dict = generate_candidate_proposals( video_list, video_infos, tem_results_dir, 5, 0.5, tem_results_ext='unsupport_ext') # test without result_dict assert_result1 = np.array([ [0.1, 0.7, 0.58390868, 0.35708317, 0.20850396, 0.55555556, 0.55555556], [0.1, 0.5, 0.58390868, 0.32605207, 0.19038463, 0.29411765, 0.41666667], [0.1, 0.3, 0.58390868, 0.26221931, 0.15311213, 0., 0.], [0.3, 0.7, 0.30626667, 0.35708317, 0.10936267, 0.83333333, 0.83333333], [0.3, 0.5, 0.30626667, 0.32605207, 0.09985888, 0.45454545, 0.83333333] ]) assert_result2 = np.array( [[0.1, 0.3, 0.78390867, 0.3622193, 0.28394685, 0., 0.], [0.1, 0.7, 0.78390867, 0.35708317, 0.27992059, 0., 0.], [0.1, 0.5, 0.78390867, 0.32605207, 0.25559504, 0., 0.]]) result_dict = generate_candidate_proposals(video_list, video_infos, tem_results_dir, 5, 0.5) assert_array_almost_equal(result_dict['v_test1'], assert_result1) assert_array_almost_equal(result_dict['v_test2'], assert_result2) # test with result_dict result_dict = {} generate_candidate_proposals( video_list, video_infos, tem_results_dir, 5, 0.5, result_dict=result_dict) assert_array_almost_equal(result_dict['v_test1'], assert_result1) assert_array_almost_equal(result_dict['v_test2'], assert_result2) def test_generate_bsp_feature(): video_list = [0, 1] video_infos = [ dict( video_name='v_test1', duration_second=100, duration_frame=1000, annotations=[{ 'segment': [30.0, 60.0], 'label': 'Rock climbing' }], feature_frame=900), dict( video_name='v_test2', duration_second=100, duration_frame=1000, annotations=[{ 'segment': [6.0, 8.0], 'label': 'Drinking beer' }], feature_frame=900) ] tem_results_dir = osp.normpath( osp.join(osp.dirname(__file__), '../../data/tem_results')) pgm_proposals_dir = osp.normpath( osp.join(osp.dirname(__file__), '../../data/proposals')) # test when extension is not valid with pytest.raises(NotImplementedError): result_dict = generate_bsp_feature( video_list, video_infos, tem_results_dir, pgm_proposals_dir, tem_results_ext='unsupport_ext') with pytest.raises(NotImplementedError): result_dict = generate_bsp_feature( video_list, video_infos, tem_results_dir, pgm_proposals_dir, pgm_proposal_ext='unsupport_ext') # test without result_dict result_dict = generate_bsp_feature( video_list, video_infos, tem_results_dir, pgm_proposals_dir, top_k=2) assert_result1 = np.array( [[ 0.02633105, 0.02489364, 0.02345622, 0.0220188, 0.02058138, 0.01914396, 0.01770654, 0.01626912, 0.01541432, 0.01514214, 0.01486995, 0.01459776, 0.01432558, 0.01405339, 0.01378121, 0.01350902, 0.03064331, 0.02941124, 0.02817916, 0.02694709, 0.02571502, 0.02448295, 0.02325087, 0.0220188, 0.01432558, 0.01409228, 0.01385897, 0.01362567, 0.01339237, 0.01315907, 0.01292577, 0.01269246 ], [ 0.01350902, 0.01323684, 0.01296465, 0.01269246, 0.01242028, 0.01214809, 0.01187591, 0.01160372, 0.01154264, 0.01169266, 0.01184269, 0.01199271, 0.01214273, 0.01229275, 0.01244278, 0.0125928, 0.01432558, 0.01409228, 0.01385897, 0.01362567, 0.01339237, 0.01315907, 0.01292577, 0.01269246, 0.01214273, 0.01227132, 0.01239991, 0.0125285, 0.0126571, 0.01278569, 0.01291428, 0.01304287 ]]) assert_result2 = np.array( [[ 0.04133105, 0.03922697, 0.03712288, 0.0350188, 0.03291471, 0.03081063, 0.02870654, 0.02660246, 0.02541432, 0.02514214, 0.02486995, 0.02459776, 0.02432558, 0.02405339, 0.02378121, 0.02350902, 0.04764331, 0.04583981, 0.04403631, 0.04223281, 0.0404293, 0.0386258, 0.0368223, 0.0350188, 0.02432558, 0.02409228, 0.02385897, 0.02362567, 0.02339237, 0.02315907, 0.02292577, 0.02269246 ], [ 0.02350902, 0.02323684, 0.02296465, 0.02269246, 0.02242028, 0.02214809, 0.02187591, 0.02160372, 0.02120931, 0.02069266, 0.02017602, 0.01965937, 0.01914273, 0.01862609, 0.01810944, 0.0175928, 0.02432558, 0.02409228, 0.02385897, 0.02362567, 0.02339237, 0.02315907, 0.02292577, 0.02269246, 0.01914273, 0.01869989, 0.01825706, 0.01781422, 0.01737138, 0.01692854, 0.0164857, 0.01604287 ]]) assert_array_almost_equal(result_dict['v_test1'], assert_result1) assert_array_almost_equal(result_dict['v_test2'], assert_result2) # test with result_dict result_dict = {} generate_bsp_feature( video_list, video_infos, tem_results_dir, pgm_proposals_dir, top_k=2, result_dict=result_dict) assert_array_almost_equal(result_dict['v_test1'], assert_result1) assert_array_almost_equal(result_dict['v_test2'], assert_result2)