gradio/test/test_processing_utils.py

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import unittest
import pathlib
import gradio as gr
from PIL import Image
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import matplotlib.pyplot as plt
import numpy as np
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import os
import tempfile
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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class ImagePreprocessing(unittest.TestCase):
def test_decode_base64_to_image(self):
output_image = gr.processing_utils.decode_base64_to_image(
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gr.test_data.BASE64_IMAGE)
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self.assertIsInstance(output_image, Image.Image)
def test_encode_url_or_file_to_base64(self):
output_base64 = gr.processing_utils.encode_url_or_file_to_base64(
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"test/test_data/test_image.png")
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self.assertEquals(output_base64, gr.test_data.BASE64_IMAGE)
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def test_encode_file_to_base64(self):
output_base64 = gr.processing_utils.encode_file_to_base64(
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"test/test_data/test_image.png")
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self.assertEquals(output_base64, gr.test_data.BASE64_IMAGE)
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def test_encode_url_to_base64(self):
output_base64 = gr.processing_utils.encode_url_to_base64(
"https://raw.githubusercontent.com/gradio-app/gradio/master/test"
"/test_data/test_image.png")
self.assertEqual(output_base64, gr.test_data.BASE64_IMAGE)
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# def test_encode_plot_to_base64(self): # Commented out because this is throwing errors on Windows. Possibly due to different matplotlib behavior on Windows?
# plt.plot([1, 2, 3, 4])
# output_base64 = gr.processing_utils.encode_plot_to_base64(plt)
# self.assertEqual(output_base64, gr.test_data.BASE64_PLT_IMG)
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def test_encode_array_to_base64(self):
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img = Image.open("test/test_data/test_image.png")
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img = img.convert("RGB")
numpy_data = np.asarray(img, dtype=np.uint8)
output_base64 = gr.processing_utils.encode_array_to_base64(numpy_data)
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self.assertEqual(output_base64, gr.test_data.ARRAY_TO_BASE64_IMAGE)
def test_resize_and_crop(self):
img = Image.open("test/test_data/test_image.png")
new_img = gr.processing_utils.resize_and_crop(img, (20, 20))
self.assertEqual(new_img.size, (20, 20))
self.assertRaises(ValueError, gr.processing_utils.resize_and_crop,
**{'img': img, 'size': (20, 20), 'crop_type': 'test'})
class AudioPreprocessing(unittest.TestCase):
def test_audio_from_file(self):
audio = gr.processing_utils.audio_from_file(
"test/test_data/test_audio.wav")
self.assertEqual(audio[0], 22050)
self.assertIsInstance(audio[1], np.ndarray)
def test_audio_to_file(self):
audio = gr.processing_utils.audio_from_file(
"test/test_data/test_audio.wav")
gr.processing_utils.audio_to_file(audio[0], audio[1], "test_audio_to_file")
self.assertTrue(os.path.exists("test_audio_to_file"))
os.remove("test_audio_to_file")
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class OutputPreprocessing(unittest.TestCase):
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def test_decode_base64_to_binary(self):
binary = gr.processing_utils.decode_base64_to_binary(
gr.test_data.BASE64_IMAGE)
self.assertEqual(gr.test_data.BINARY_IMAGE, binary)
def test_decode_base64_to_file(self):
temp_file = gr.processing_utils.decode_base64_to_file(
gr.test_data.BASE64_IMAGE)
self.assertIsInstance(temp_file, tempfile._TemporaryFileWrapper)
def test_create_tmp_copy_of_file(self):
temp_file = gr.processing_utils.create_tmp_copy_of_file(
"test.txt")
self.assertIsInstance(temp_file, tempfile._TemporaryFileWrapper)
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float_dtype_list = [float, float, np.double, np.single, np.float32,
np.float64, 'float32', 'float64']
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def test_float_conversion_dtype(self):
"""Test any convertion from a float dtype to an other."""
x = np.array([-1, 1])
# Test all combinations of dtypes conversions
dtype_combin = np.array(np.meshgrid(
OutputPreprocessing.float_dtype_list,
OutputPreprocessing.float_dtype_list)).T.reshape(-1, 2)
for dtype_in, dtype_out in dtype_combin:
x = x.astype(dtype_in)
y = gr.processing_utils._convert(x, dtype_out)
assert y.dtype == np.dtype(dtype_out)
def test_subclass_conversion(self):
"""Check subclass conversion behavior"""
x = np.array([-1, 1])
for dtype in OutputPreprocessing.float_dtype_list:
x = x.astype(dtype)
y = gr.processing_utils._convert(x, np.floating)
assert y.dtype == x.dtype
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if __name__ == '__main__':
unittest.main()