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47 lines
2.1 KiB
Python
47 lines
2.1 KiB
Python
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import unittest
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import gradio.interpretation
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import gradio.test_data
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from gradio.processing_utils import decode_base64_to_image
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from gradio import Interface
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import numpy as np
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class TestDefault(unittest.TestCase):
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def setUp(self):
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self.default_method = gradio.interpretation.default()
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def test_default_text(self):
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max_word_len = lambda text: max([len(word) for word in text.split(" ")])
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text_interface = Interface(max_word_len, "textbox", "label")
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interpretation = self.default_method(text_interface, ["quickest brown fox"])[0]
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self.assertGreater(interpretation[0][1], 0) # Checks to see if the first letter has >0 score.
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self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last letter has 0 score.
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def test_default_image(self):
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max_pixel_value = lambda img: img.max()
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img_interface = Interface(max_pixel_value, "image", "label")
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array = np.zeros((100,100))
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array[0, 0] = 1
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interpretation = self.default_method(img_interface, [array])[0]
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self.assertGreater(interpretation[0][0], 0) # Checks to see if the top-left has >0 score.
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class TestCustom(unittest.TestCase):
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def test_custom_text(self):
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max_word_len = lambda text: max([len(word) for word in text.split(" ")])
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custom = lambda text: [(char, 1) for char in text]
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text_interface = Interface(max_word_len, "textbox", "label", interpretation=custom)
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result = text_interface.interpret(["quickest brown fox"])[0]
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self.assertEqual(result[0][1], 1) # Checks to see if the first letter has score of 1.
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def test_custom_img(self):
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max_pixel_value = lambda img: img.max()
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custom = lambda img: img.tolist()
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img_interface = Interface(max_pixel_value, "image", "label", interpretation=custom)
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result = img_interface.interpret([gradio.test_data.BASE64_IMAGE])[0]
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expected_result = np.asarray(decode_base64_to_image(gradio.test_data.BASE64_IMAGE).convert('RGB')).tolist()
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self.assertEqual(result, expected_result)
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if __name__ == '__main__':
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unittest.main()
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