import unittest
import gradio as gr
import numpy as np
import pandas as pd
import tempfile
class TestTextbox(unittest.TestCase):
def test_in_interface(self):
iface = gr.Interface(lambda x: x[-1], "textbox", gr.outputs.Textbox())
self.assertEqual(iface.process(["Hello"])[0], ["o"])
iface = gr.Interface(lambda x: x / 2, "number", gr.outputs.Textbox(type="number"))
self.assertEqual(iface.process([10])[0], [5])
class TestLabel(unittest.TestCase):
def test_as_component(self):
y = 'happy'
label_output = gr.outputs.Label()
label = label_output.postprocess(y)
self.assertDictEqual(label, {"label": "happy"})
y = {
3: 0.7,
1: 0.2,
0: 0.1
}
label_output = gr.outputs.Label()
label = label_output.postprocess(y)
self.assertDictEqual(label, {
"label": 3,
"confidences": [
{"label": 3, "confidence": 0.7},
{"label": 1, "confidence": 0.2},
{"label": 0, "confidence": 0.1},
]
})
def test_in_interface(self):
x_img = gr.test_data.BASE64_IMAGE
def rgb_distribution(img):
rgb_dist = np.mean(img, axis=(0, 1))
rgb_dist /= np.sum(rgb_dist)
rgb_dist = np.round(rgb_dist, decimals=2)
return {
"red": rgb_dist[0],
"green": rgb_dist[1],
"blue": rgb_dist[2],
}
iface = gr.Interface(rgb_distribution, "image", "label")
output = iface.process([x_img])[0][0]
self.assertDictEqual(output, {
'label': 'red',
'confidences': [
{'label': 'red', 'confidence': 0.44},
{'label': 'green', 'confidence': 0.28},
{'label': 'blue', 'confidence': 0.28}
]
})
class TestImage(unittest.TestCase):
def test_as_component(self):
y_img = gr.processing_utils.decode_base64_to_image(gr.test_data.BASE64_IMAGE)
image_output = gr.outputs.Image()
self.assertTrue(image_output.postprocess(y_img)[0].startswith("data:image/png;base64,iVBORw0KGgoAAA"))
self.assertTrue(image_output.postprocess(np.array(y_img))[0].startswith("data:image/png;base64,iVBORw0KGgoAAA"))
def test_in_interface(self):
def generate_noise(width, height):
return np.random.randint(0, 256, (width, height, 3))
iface = gr.Interface(generate_noise, ["slider", "slider"], "image")
self.assertTrue(iface.process([10, 20])[0][0][0].startswith("data:image/png;base64"))
class TestKeyValues(unittest.TestCase):
def test_in_interface(self):
def letter_distribution(word):
dist = {}
for letter in word:
dist[letter] = dist.get(letter, 0) + 1
return dist
iface = gr.Interface(letter_distribution, "text", "key_values")
self.assertListEqual(iface.process(["alpaca"])[0][0], [
("a", 3), ("l", 1), ("p", 1), ("c", 1)])
class TestHighlightedText(unittest.TestCase):
def test_in_interface(self):
def highlight_vowels(sentence):
phrases, cur_phrase = [], ""
vowels, mode = "aeiou", None
for letter in sentence:
letter_mode = "vowel" if letter in vowels else "non"
if mode is None:
mode = letter_mode
elif mode != letter_mode:
phrases.append((cur_phrase, mode))
cur_phrase = ""
mode = letter_mode
cur_phrase += letter
phrases.append((cur_phrase, mode))
return phrases
iface = gr.Interface(highlight_vowels, "text", "highlight")
self.assertListEqual(iface.process(["Helloooo"])[0][0], [
("H", "non"), ("e", "vowel"), ("ll", "non"), ("oooo", "vowel")])
class TestAudio(unittest.TestCase):
def test_as_component(self):
y_audio = gr.processing_utils.decode_base64_to_file(gr.test_data.BASE64_AUDIO)
audio_output = gr.outputs.Audio(type="file")
self.assertTrue(audio_output.postprocess(y_audio.name).startswith("data:audio/wav;base64,UklGRuI/AABXQVZFZm10IBAAA"))
def test_in_interface(self):
def generate_noise(duration):
return 8000, np.random.randint(-256, 256, (duration, 3))
iface = gr.Interface(generate_noise, "slider", "audio")
self.assertTrue(iface.process([100])[0][0].startswith("data:audio/wav;base64"))
class TestJSON(unittest.TestCase):
def test_in_interface(self):
def get_avg_age_per_gender(data):
return {
"M": int(data[data["gender"] == "M"].mean()),
"F": int(data[data["gender"] == "F"].mean()),
"O": int(data[data["gender"] == "O"].mean()),
}
iface = gr.Interface(
get_avg_age_per_gender,
gr.inputs.Dataframe(headers=["gender", "age"]),
"json")
y_data = [
["M", 30],
["F", 20],
["M", 40],
["O", 20],
["F", 30],
]
self.assertDictEqual(iface.process([y_data])[0][0], {
"M": 35, "F": 25, "O": 20
})
class TestHTML(unittest.TestCase):
def test_in_interface(self):
def bold_text(text):
return "" + text + ""
iface = gr.Interface(bold_text, "text", "html")
self.assertEqual(iface.process(["test"])[0][0], "test")
class TestFile(unittest.TestCase):
def test_as_component(self):
def write_file(content):
with open("test.txt", "w") as f:
f.write(content)
return "test.txt"
iface = gr.Interface(write_file, "text", "file")
self.assertDictEqual(iface.process(["hello world"])[0][0], {
'name': 'test.txt', 'size': 11, 'data': 'aGVsbG8gd29ybGQ='
})
class TestDataframe(unittest.TestCase):
def test_as_component(self):
dataframe_output = gr.outputs.Dataframe()
output = dataframe_output.postprocess(np.zeros((2,2)))
self.assertDictEqual(output, {"data": [[0,0],[0,0]]})
output = dataframe_output.postprocess([[1,3,5]])
self.assertDictEqual(output, {"data": [[1, 3, 5]]})
output = dataframe_output.postprocess(pd.DataFrame(
[[2, True], [3, True], [4, False]], columns=["num", "prime"]))
self.assertDictEqual(output,
{"headers": ["num", "prime"], "data": [[2, True], [3, True], [4, False]]})
def test_in_interface(self):
def check_odd(array):
return array % 2 == 0
iface = gr.Interface(check_odd, "numpy", "numpy")
self.assertEqual(
iface.process([[2, 3, 4]])[0][0],
{"data": [[True, False, True]]})
if __name__ == '__main__':
unittest.main()