# 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.localization 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)
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