mirror of
https://github.com/wassname/IndicoIo-python.git
synced 2026-06-27 16:10:34 +08:00
Madison May
235 lines
8.0 KiB
Python
235 lines
8.0 KiB
Python
import unittest
|
|
import os
|
|
from requests import ConnectionError
|
|
|
|
import numpy as np
|
|
import skimage.io
|
|
from nose.plugins.skip import Skip, SkipTest
|
|
|
|
from indicoio import config
|
|
from indicoio import political, sentiment, fer, facial_features, language, image_features, text_tags
|
|
from indicoio import batch_political, batch_sentiment, batch_fer, batch_facial_features
|
|
from indicoio import batch_language, batch_image_features, batch_text_tags
|
|
|
|
DIR = os.path.dirname(os.path.realpath(__file__))
|
|
|
|
class BatchAPIRun(unittest.TestCase):
|
|
|
|
def setUp(self):
|
|
self.auth = config.auth
|
|
|
|
if not all(self.auth):
|
|
raise SkipTest
|
|
|
|
def test_batch_texttags(self):
|
|
test_data = ["On Monday, president Barack Obama will be..."]
|
|
response = batch_text_tags(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
|
|
def test_batch_posneg(self):
|
|
test_data = ['Worst song ever', 'Best song ever']
|
|
response = batch_sentiment(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(response[0] < 0.5)
|
|
|
|
def test_batch_political(self):
|
|
test_data = ["Guns don't kill people, people kill people."]
|
|
response = batch_political(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
|
|
def test_batch_fer(self):
|
|
test_data = [np.random.rand(48, 48).tolist()]
|
|
response = batch_fer(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(isinstance(response[0], dict))
|
|
|
|
def test_batch_facial_features(self):
|
|
test_data = [np.random.rand(48, 48).tolist()]
|
|
response = batch_facial_features(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(isinstance(response[0], list))
|
|
self.assertEqual(len(response[0]), 48)
|
|
|
|
def test_batch_image_features_greyscale(self):
|
|
test_data = [np.random.rand(64, 64).tolist()]
|
|
response = batch_image_features(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(isinstance(response[0], list))
|
|
self.assertEqual(len(response[0]), 2048)
|
|
|
|
def test_batch_image_features_rgb(self):
|
|
test_data = [np.random.rand(64, 64, 3).tolist()]
|
|
response = batch_image_features(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(isinstance(response[0], list))
|
|
self.assertEqual(len(response[0]), 2048)
|
|
|
|
def test_batch_language(self):
|
|
test_data = ['clearly an english sentence']
|
|
response = batch_language(test_data, auth=self.auth)
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertTrue(response[0]['English'] > 0.25)
|
|
|
|
def test_batch_set_cloud(self):
|
|
test_data = ['clearly an english sentence']
|
|
self.assertRaises(ConnectionError,
|
|
batch_language,
|
|
test_data,
|
|
auth=self.auth,
|
|
cloud='invalid/cloud')
|
|
|
|
|
|
class FullAPIRun(unittest.TestCase):
|
|
|
|
def load_image(self, relpath, as_grey=False):
|
|
image_path = os.path.normpath(os.path.join(DIR, relpath))
|
|
image = skimage.io.imread(image_path, as_grey=True).tolist()
|
|
return image
|
|
|
|
def check_range(self, list, minimum=0.9, maximum=0.1, span=0.5):
|
|
vector = np.asarray(list)
|
|
self.assertTrue(vector.max() > maximum)
|
|
self.assertTrue(vector.min() < minimum)
|
|
self.assertTrue(np.ptp(vector) > span)
|
|
|
|
def test_text_tags(self):
|
|
text = "On Monday, president Barack Obama will be..."
|
|
results = text_tags(text)
|
|
max_keys = sorted(results.keys(), key=lambda x:results.get(x), reverse=True)
|
|
assert 'political_discussion' in max_keys[:5]
|
|
results = text_tags(text, top_n=5)
|
|
assert len(results) is 5
|
|
results = text_tags(text, threshold=0.1)
|
|
for v in results.values():
|
|
assert v >= 0.1
|
|
|
|
def test_political(self):
|
|
political_set = set(['Libertarian', 'Liberal', 'Conservative', 'Green'])
|
|
test_string = "Guns don't kill people, people kill people."
|
|
response = political(test_string)
|
|
|
|
self.assertTrue(isinstance(response, dict))
|
|
self.assertEqual(political_set, set(response.keys()))
|
|
|
|
test_string = "Save the whales"
|
|
response = political(test_string)
|
|
|
|
self.assertTrue(isinstance(response, dict))
|
|
assert response['Green'] > 0.5
|
|
|
|
def test_posneg(self):
|
|
test_string = "Worst song ever."
|
|
response = sentiment(test_string)
|
|
|
|
self.assertTrue(isinstance(response, float))
|
|
self.assertTrue(response < 0.5)
|
|
|
|
test_string = "Best song ever."
|
|
response = sentiment(test_string)
|
|
self.assertTrue(isinstance(response, float))
|
|
self.assertTrue(response > 0.5)
|
|
|
|
def test_good_fer(self):
|
|
fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
|
|
test_face = np.random.rand(48,48).tolist()
|
|
response = fer(test_face)
|
|
|
|
self.assertTrue(isinstance(response, dict))
|
|
self.assertEqual(fer_set, set(response.keys()))
|
|
|
|
def test_happy_fer(self):
|
|
test_face = self.load_image("data/happy.png", as_grey=True)
|
|
response = fer(test_face)
|
|
self.assertTrue(isinstance(response, dict))
|
|
self.assertTrue(response['Happy'] > 0.5)
|
|
|
|
def test_fear_fer(self):
|
|
test_face = self.load_image("data/fear.png", as_grey=True)
|
|
response = fer(test_face)
|
|
self.assertTrue(isinstance(response, dict))
|
|
self.assertTrue(response['Fear'] > 0.25)
|
|
|
|
def test_bad_fer(self):
|
|
fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
|
|
test_face = np.random.rand(56,56).tolist()
|
|
response = fer(test_face)
|
|
|
|
self.assertTrue(isinstance(response, dict))
|
|
self.assertEqual(fer_set, set(response.keys()))
|
|
|
|
def test_good_facial_features(self):
|
|
test_face = np.random.rand(48,48).tolist()
|
|
response = facial_features(test_face)
|
|
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertEqual(len(response), 48)
|
|
self.check_range(response)
|
|
|
|
def test_good_image_features_greyscale(self):
|
|
test_image = np.random.rand(64, 64).tolist()
|
|
response = image_features(test_image)
|
|
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertEqual(len(response), 2048)
|
|
self.check_range(response)
|
|
|
|
def test_good_image_features_rgb(self):
|
|
test_image = np.random.rand(64, 64, 3).tolist()
|
|
response = image_features(test_image)
|
|
|
|
self.assertTrue(isinstance(response, list))
|
|
self.assertEqual(len(response), 2048)
|
|
self.check_range(response)
|
|
|
|
def test_language(self):
|
|
language_set = set([
|
|
'English',
|
|
'Spanish',
|
|
'Tagalog',
|
|
'Esperanto',
|
|
'French',
|
|
'Chinese',
|
|
'French',
|
|
'Bulgarian',
|
|
'Latin',
|
|
'Slovak',
|
|
'Hebrew',
|
|
'Russian',
|
|
'German',
|
|
'Japanese',
|
|
'Korean',
|
|
'Portuguese',
|
|
'Italian',
|
|
'Polish',
|
|
'Turkish',
|
|
'Dutch',
|
|
'Arabic',
|
|
'Persian (Farsi)',
|
|
'Czech',
|
|
'Swedish',
|
|
'Indonesian',
|
|
'Vietnamese',
|
|
'Romanian',
|
|
'Greek',
|
|
'Danish',
|
|
'Hungarian',
|
|
'Thai',
|
|
'Finnish',
|
|
'Norwegian',
|
|
'Lithuanian'
|
|
])
|
|
language_dict = language('clearly an english sentence')
|
|
self.assertEqual(language_set, set(language_dict.keys()))
|
|
assert language_dict['English'] > 0.25
|
|
|
|
def test_set_cloud(self):
|
|
test_data = 'clearly an english sentence'
|
|
self.assertRaises(ConnectionError,
|
|
language,
|
|
test_data,
|
|
cloud='invalid/cloud')
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|