mirror of
https://github.com/gradio-app/gradio.git
synced 2024-12-09 02:00:44 +08:00
129 lines
4.5 KiB
Python
129 lines
4.5 KiB
Python
import os
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import pathlib
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import tempfile
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import unittest
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import matplotlib.pyplot as plt
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import numpy as np
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from PIL import Image
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import gradio as gr
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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class ImagePreprocessing(unittest.TestCase):
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def test_decode_base64_to_image(self):
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output_image = gr.processing_utils.decode_base64_to_image(
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gr.test_data.BASE64_IMAGE
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)
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self.assertIsInstance(output_image, Image.Image)
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def test_encode_url_or_file_to_base64(self):
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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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)
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self.assertEquals(output_base64, gr.test_data.BASE64_IMAGE)
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def test_encode_file_to_base64(self):
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output_base64 = gr.processing_utils.encode_file_to_base64(
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"test/test_data/test_image.png"
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)
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self.assertEquals(output_base64, gr.test_data.BASE64_IMAGE)
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def test_encode_url_to_base64(self):
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output_base64 = gr.processing_utils.encode_url_to_base64(
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"https://raw.githubusercontent.com/gradio-app/gradio/master/test"
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"/test_data/test_image.png"
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)
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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?
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# plt.plot([1, 2, 3, 4])
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# output_base64 = gr.processing_utils.encode_plot_to_base64(plt)
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# 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")
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numpy_data = np.asarray(img, dtype=np.uint8)
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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)
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def test_resize_and_crop(self):
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img = Image.open("test/test_data/test_image.png")
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new_img = gr.processing_utils.resize_and_crop(img, (20, 20))
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self.assertEqual(new_img.size, (20, 20))
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self.assertRaises(
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ValueError,
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gr.processing_utils.resize_and_crop,
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**{"img": img, "size": (20, 20), "crop_type": "test"}
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)
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class AudioPreprocessing(unittest.TestCase):
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def test_audio_from_file(self):
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audio = gr.processing_utils.audio_from_file("test/test_data/test_audio.wav")
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self.assertEqual(audio[0], 22050)
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self.assertIsInstance(audio[1], np.ndarray)
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def test_audio_to_file(self):
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audio = gr.processing_utils.audio_from_file("test/test_data/test_audio.wav")
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gr.processing_utils.audio_to_file(audio[0], audio[1], "test_audio_to_file")
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self.assertTrue(os.path.exists("test_audio_to_file"))
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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):
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binary = gr.processing_utils.decode_base64_to_binary(gr.test_data.BASE64_IMAGE)
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self.assertEqual(gr.test_data.BINARY_IMAGE, binary)
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def test_decode_base64_to_file(self):
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temp_file = gr.processing_utils.decode_base64_to_file(gr.test_data.BASE64_IMAGE)
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self.assertIsInstance(temp_file, tempfile._TemporaryFileWrapper)
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def test_create_tmp_copy_of_file(self):
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temp_file = gr.processing_utils.create_tmp_copy_of_file("test.txt")
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self.assertIsInstance(temp_file, tempfile._TemporaryFileWrapper)
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float_dtype_list = [
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float,
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float,
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np.double,
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np.single,
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np.float32,
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np.float64,
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"float32",
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"float64",
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]
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def test_float_conversion_dtype(self):
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"""Test any convertion from a float dtype to an other."""
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x = np.array([-1, 1])
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# Test all combinations of dtypes conversions
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dtype_combin = np.array(
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np.meshgrid(
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OutputPreprocessing.float_dtype_list,
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OutputPreprocessing.float_dtype_list,
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)
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).T.reshape(-1, 2)
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for dtype_in, dtype_out in dtype_combin:
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x = x.astype(dtype_in)
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y = gr.processing_utils._convert(x, dtype_out)
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assert y.dtype == np.dtype(dtype_out)
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def test_subclass_conversion(self):
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"""Check subclass conversion behavior"""
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x = np.array([-1, 1])
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for dtype in OutputPreprocessing.float_dtype_list:
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x = x.astype(dtype)
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y = gr.processing_utils._convert(x, np.floating)
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assert y.dtype == x.dtype
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if __name__ == "__main__":
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unittest.main()
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