mirror of
https://github.com/gradio-app/gradio.git
synced 2024-12-09 02:00:44 +08:00
45 lines
2.1 KiB
Python
45 lines
2.1 KiB
Python
import unittest
|
|
import gradio.interpretation
|
|
import gradio.test_data
|
|
from gradio.processing_utils import decode_base64_to_image, encode_array_to_base64
|
|
from gradio import Interface
|
|
import numpy as np
|
|
|
|
|
|
class TestDefault(unittest.TestCase):
|
|
def test_default_text(self):
|
|
max_word_len = lambda text: max([len(word) for word in text.split(" ")])
|
|
text_interface = Interface(max_word_len, "textbox", "label", interpretation="default")
|
|
interpretation = text_interface.interpret(["quickest brown fox"])[0][0]
|
|
self.assertGreater(interpretation[0][1], 0) # Checks to see if the first word has >0 score.
|
|
self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
|
|
|
|
def test_default_image(self):
|
|
max_pixel_value = lambda img: img.max()
|
|
img_interface = Interface(max_pixel_value, "image", "number", interpretation="default")
|
|
array = np.zeros((100,100))
|
|
array[0, 0] = 1
|
|
img = encode_array_to_base64(array)
|
|
interpretation = img_interface.interpret([img])[0][0]
|
|
self.assertGreater(interpretation[0][0], 0) # Checks to see if the top-left has >0 score.
|
|
|
|
|
|
class TestCustom(unittest.TestCase):
|
|
def test_custom_text(self):
|
|
max_word_len = lambda text: max([len(word) for word in text.split(" ")])
|
|
custom = lambda text: [(char, 1) for char in text]
|
|
text_interface = Interface(max_word_len, "textbox", "label", interpretation=custom)
|
|
result = text_interface.interpret(["quickest brown fox"])[0][0]
|
|
self.assertEqual(result[0][1], 1) # Checks to see if the first letter has score of 1.
|
|
|
|
def test_custom_img(self):
|
|
max_pixel_value = lambda img: img.max()
|
|
custom = lambda img: img.tolist()
|
|
img_interface = Interface(max_pixel_value, "image", "label", interpretation=custom)
|
|
result = img_interface.interpret([gradio.test_data.BASE64_IMAGE])[0][0]
|
|
expected_result = np.asarray(decode_base64_to_image(gradio.test_data.BASE64_IMAGE).convert('RGB')).tolist()
|
|
self.assertEqual(result, expected_result)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main() |