def test_big_pipeline():
pytest.importorskip('pygraphviz')
filename = join(get_test_data_path(), 'video', 'obama_speech.mp4')
video = VideoStim(filename)
visual_nodes = [(FrameSamplingFilter(every=15), [
(TesseractConverter(), [LengthExtractor()]),
VibranceExtractor(),
'BrightnessExtractor',
])]
audio_nodes = [(VideoToAudioConverter(),
[WitTranscriptionConverter(),
'LengthExtractor'], 'video_to_audio')]
graph = Graph()
graph.add_nodes(visual_nodes)
graph.add_nodes(audio_nodes)
results = graph.run(video, merge=False)
result = merge_results(results, format='wide', extractor_names='multi')
# Test that pygraphviz outputs a file
drawfile = next(tempfile._get_candidate_names())
graph.draw(drawfile)
assert exists(drawfile)
os.remove(drawfile)
assert ('LengthExtractor', 'text_length') in result.columns
assert ('VibranceExtractor', 'vibrance') in result.columns
# assert not result[('onset', '')].isnull().any()
assert 'text[negotiations]' in result['stim_name'].values
assert 'frame[90]' in result['stim_name'].values
def test_small_pipeline_json_spec3():
pytest.importorskip('pytesseract')
filename = join(get_test_data_path(), 'image', 'button.jpg')
stim = ImageStim(filename)
nodes = {
"roots": [{
"transformer": "GoogleVisionAPITextConverter",
"parameters": {
"num_retries": 5,
"max_results": 10
},
"children": [{
"transformer": "LengthExtractor"
}]
}]
}
graph = Graph(nodes)
result = list(graph.run([stim], merge=False))
history = result[0].history.to_df()
assert history.shape == (2, 8)
assert history.iloc[0]['result_class'] == 'TextStim'
result = merge_results(result, format='wide', extractor_names='multi')
assert (0, 'text[Exit\n]') in result['stim_name'].values
assert ('LengthExtractor', 'text_length') in result.columns
assert result[('LengthExtractor', 'text_length')].values[0] == 4
def test_graph_smoke_test():
filename = join(get_test_data_path(), 'image', 'obama.jpg')
stim = ImageStim(filename)
nodes = [(BrightnessExtractor(), [], 'brightness_node')]
graph = Graph(nodes)
result = graph.run(stim, format='wide', extractor_names='multi')
brightness = result[('brightness_node', 'brightness')].values[0]
assert_almost_equal(brightness, 0.556134, 5)
def test_stim_results():
stim = TextStim(text='some, example the text.')
g = Graph()
g.add_nodes(
['PunctuationRemovalFilter', 'TokenRemovalFilter', 'TokenizingFilter'],
mode='vertical')
final_stims = g.run(stim, merge=False)
assert len(final_stims) == 2
assert final_stims[1].text == 'text'
n = Node('PunctuationRemovalFilter', name='punc')
g = Graph([n])
g.add_nodes(['TokenizingFilter', 'LengthExtractor'], parent=n)
results = g.run(stim)
assert isinstance(results, pd.DataFrame)
assert results['LengthExtractor#text_length'][0] == 21
with pytest.raises(ValueError):
g.run(stim, invalid_results='fail')
def test_convert_to_long_graph():
image_dir = join(get_test_data_path(), 'image')
stim = ImageStim(join(image_dir, 'obama.jpg'))
ext = GoogleVisionAPIFaceExtractor()
g = Graph([ext])
timeline = g.run(stim)
long_timeline = to_long_format(timeline)
assert 'feature' in long_timeline.columns
assert 'extractor' in long_timeline.columns
assert 'history' in long_timeline.columns
def test_save_graph():
graph = Graph(
spec=join(get_test_data_path(), 'graph', 'simple_graph.json'))
filename = tempfile.mkstemp()[1]
graph.save(filename)
assert os.path.exists(filename)
same_graph = Graph(spec=filename)
os.remove(filename)
assert graph.to_json() == same_graph.to_json()
img = join(get_test_data_path(), 'image', 'button.jpg')
res = same_graph.run(img)
assert res['LengthExtractor#text_length'][0] == 4
def test_adding_nodes():
graph = Graph()
graph.add_children(['VibranceExtractor', 'BrightnessExtractor'])
assert len(graph.roots) == 2
assert len(graph.nodes) == 2
for r in graph.roots:
assert len(r.children) == 0
img = ImageStim(join(get_test_data_path(), 'image', 'button.jpg'))
results = graph.run(img, merge=False)
assert len(results) == 2
assert_almost_equal(results[0].to_df()['vibrance'][0], 841.577274, 5)
assert_almost_equal(results[1].to_df()['brightness'][0], 0.746965, 5)
graph = Graph()
graph.add_chain(['PunctuationRemovalFilter', 'LengthExtractor'])
txt = TextStim(text='the.best.text.')
results = graph.run(txt, merge=False)
assert len(results) == 1
assert results[0].to_df()['text_length'][0] == 11
with pytest.raises(ValueError):
graph.add_nodes(['LengthExtractor'], mode='invalid')
def test_small_pipeline2():
filename = join(get_test_data_path(), 'image', 'button.jpg')
nodes = [BrightnessExtractor(), VibranceExtractor()]
graph = Graph(nodes)
result = list(graph.run([filename], merge=False))
history = result[0].history.to_df()
assert history.shape == (1, 8)
result = merge_results(result, format='wide', extractor_names='multi')
assert ('BrightnessExtractor', 'brightness') in result.columns
brightness = result[('BrightnessExtractor', 'brightness')].values[0]
vibrance = result[('VibranceExtractor', 'vibrance')].values[0]
assert_almost_equal(brightness, 0.746965, 5)
assert ('VibranceExtractor', 'vibrance') in result.columns
assert_almost_equal(vibrance, 841.577274, 5)
def test_small_pipeline():
pytest.importorskip('pytesseract')
filename = join(get_test_data_path(), 'image', 'button.jpg')
stim = ImageStim(filename)
nodes = [(TesseractConverter(), [LengthExtractor()])]
graph = Graph(nodes)
result = list(graph.run([stim], merge=False))
history = result[0].history.to_df()
assert history.shape == (2, 8)
assert history.iloc[0]['result_class'] == 'TextStim'
result = merge_results(result, format='wide', extractor_names='prepend')
assert (0, 'text[Exit]') in result['stim_name'].values
assert 'LengthExtractor#text_length' in result.columns
assert result['LengthExtractor#text_length'].values[0] == 4
def test_small_pipeline_json_spec2():
pytest.importorskip('pytesseract')
filename = join(get_test_data_path(), 'image', 'button.jpg')
stim = ImageStim(filename)
spec = join(get_test_data_path(), 'graph', 'simple_graph.json')
graph = Graph(spec=spec)
result = list(graph.run([stim], merge=False))
history = result[0].history.to_df()
assert history.shape == (2, 8)
assert history.iloc[0]['result_class'] == 'TextStim'
result = merge_results(result, format='wide', extractor_names='multi')
assert (0, 'text[Exit]') in result['stim_name'].values
assert ('LengthExtractor', 'text_length') in result.columns
assert result[('LengthExtractor', 'text_length')].values[0] == 4
def test_big_pipeline_json():
pytest.importorskip('pygraphviz')
filename = join(get_test_data_path(), 'video', 'obama_speech.mp4')
video = VideoStim(filename)
nodes = {
"roots": [{
"transformer":
"FrameSamplingFilter",
"parameters": {
"every": 15
},
"children": [{
"transformer": "TesseractConverter",
"children": [{
"transformer": "LengthExtractor"
}]
}, {
"transformer": "VibranceExtractor"
}, {
"transformer": "BrightnessExtractor"
}]
}, {
"transformer":
"VideoToAudioConverter",
"children": [{
"transformer": "WitTranscriptionConverter",
"children": [{
"transformer": "LengthExtractor"
}]
}]
}]
}
graph = Graph(nodes)
results = graph.run(video, merge=False)
result = merge_results(results, format='wide', extractor_names='multi')
# Test that pygraphviz outputs a file
drawfile = next(tempfile._get_candidate_names())
graph.draw(drawfile)
assert exists(drawfile)
os.remove(drawfile)
assert ('LengthExtractor', 'text_length') in result.columns
assert ('VibranceExtractor', 'vibrance') in result.columns
# assert not result[('onset', '')].isnull().any()
assert 'text[negotiations]' in result['stim_name'].values
assert 'frame[90]' in result['stim_name'].values
def test_to_json():
nodes = {
"roots": [{
"transformer":
"FrameSamplingFilter",
"parameters": {
"every": 15
},
"children": [{
"transformer": "TesseractConverter",
"children": [{
"transformer": "LengthExtractor"
}]
}, {
"transformer": "VibranceExtractor"
}, {
"transformer": "BrightnessExtractor"
}]
}, {
"transformer":
"VideoToAudioConverter",
"children": [{
"transformer": "WitTranscriptionConverter",
"children": [{
"transformer": "LengthExtractor"
}]
}]
}]
}
graph = Graph(nodes)
assert graph.to_json() == nodes
graph = Graph(
spec=join(get_test_data_path(), 'graph', 'simple_graph.json'))
simple_graph = {
"roots": [{
"transformer": "TesseractConverter",
"children": [{
"transformer": "LengthExtractor"
}]
}]
}
assert graph.to_json() == simple_graph
filename = join(get_test_data_path(), 'image', 'button.jpg')
res = graph.run(filename)
assert res['LengthExtractor#text_length'][0] == 4
def test_big_pipeline():
filename = join(get_test_data_path(), 'video', 'obama_speech.mp4')
video = VideoStim(filename)
visual_nodes = [(FrameSamplingConverter(every=15), [
(TesseractConverter(), [LengthExtractor()]),
VibranceExtractor(), 'BrightnessExtractor',
])]
audio_nodes = [(VideoToAudioConverter(), [
WitTranscriptionConverter(), 'LengthExtractor'],
'video_to_audio')]
graph = Graph()
graph.add_nodes(visual_nodes)
graph.add_nodes(audio_nodes)
result = graph.run(video)
assert ('LengthExtractor', 'text_length') in result.columns
assert ('VibranceExtractor', 'vibrance') in result.columns
# assert not result[('onset', '')].isnull().any()
assert 'text[negotiations]' in result['stim'].values
assert 'frame[90]' in result['stim'].values
def test_small_pipeline_json_spec():
pytest.importorskip('pytesseract')
filename = join(get_test_data_path(), 'image', 'button.jpg')
stim = ImageStim(filename)
nodes = {
"roots": [{
"transformer":
"TesseractConverter",
"children": [{
"transformer": "LengthExtractor",
"children": []
}]
}]
}
graph = Graph(nodes)
result = list(graph.run([stim], merge=False))
history = result[0].history.to_df()
assert history.shape == (2, 8)
assert history.iloc[0]['result_class'] == 'TextStim'
result = merge_results(result)
assert (0, 'text[Exit]') in result['stim_name'].values
assert ('LengthExtractor', 'text_length') in result.columns
assert result[('LengthExtractor', 'text_length')].values[0] == 4
