def test_fall_detection_2_frame_back_case_2():
"""
Expected to detect a fall using frame[t] and frame[t-2].
frame[t-2] : A person is in standing position.
frame[t-1] : A person is mid-way of fall.
frame[t] : A person is fall down.
"""
config = _fall_detect_config()
result = None
def sample_callback(image=None, inference_result=None, **kwargs):
nonlocal result
result = inference_result
fall_detector = FallDetector(**config)
output = _OutPipeElement(sample_callback=sample_callback)
fall_detector.connect_to_next_element(output)
# A frame at t-2 timestamp when person is in standing position.
img_1 = _get_image(file_name='fall_img_1.png')
# A frame at t-1 timestamp when person is mid-way of fall.
img_2 = _get_image(file_name='fall_img_2_2.png')
# A frame at t timestamp when person falls down.
img_3 = _get_image(file_name='fall_img_2.png')
fall_detector.min_time_between_frames = 0.01
fall_detector.max_time_between_frames = 15
fall_detector.receive_next_sample(image=img_1)
time.sleep(fall_detector.min_time_between_frames)
fall_detector.receive_next_sample(image=img_2)
time.sleep(fall_detector.min_time_between_frames)
assert not result
fall_detector.receive_next_sample(image=img_3)
assert result
assert len(result) == 1
category = result[0]['label']
confidence = result[0]['confidence']
angle = result[0]['leaning_angle']
keypoint_corr = result[0]['keypoint_corr']
assert keypoint_corr
assert category == 'FALL'
assert confidence > 0.7
assert angle > 60
def test_fall_detection_2_frame_back_case_3():
"""
Expected to not detect a fall using frame[t],frame[t-1] and frame[t-2].
frame[t-2] : A person is in walking postion.
frame[t-1] : A person is in walking postion.
frame[t] : A person is slight in lean postion but no fall.
"""
config = _fall_detect_config()
result = None
def sample_callback(image=None, inference_result=None, **kwargs):
nonlocal result
result = inference_result
fall_detector = FallDetector(**config)
output = _OutPipeElement(sample_callback=sample_callback)
fall_detector.connect_to_next_element(output)
# A frame at t-2 timestamp when person is in walking postion.
img_1 = _get_image(file_name="fall_img_15.png")
# A frame at t-1 timestamp when person is in walking postion.
img_2 = _get_image(file_name="fall_img_16.png")
# A frame at t timestamp when person is slight in lean postion but no fall.
img_3 = _get_image(file_name="fall_img_17.png")
fall_detector.min_time_between_frames = 0.01
fall_detector.receive_next_sample(image=img_1)
time.sleep(fall_detector.min_time_between_frames)
fall_detector.receive_next_sample(image=img_2)
time.sleep(fall_detector.min_time_between_frames)
assert not result
fall_detector.receive_next_sample(image=img_3)
assert not result