本文整理匯總了Python中object_detection.core.preprocessor.random_rgb_to_gray方法的典型用法代碼示例。如果您正苦於以下問題：Python preprocessor.random_rgb_to_gray方法的具體用法？Python preprocessor.random_rgb_to_gray怎麽用？Python preprocessor.random_rgb_to_gray使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類object_detection.core.preprocessor的用法示例。
在下文中一共展示了preprocessor.random_rgb_to_gray方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: testRandomRGBtoGray
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_rgb_to_gray [as 別名]
def testRandomRGBtoGray(self):
preprocess_options = [(preprocessor.random_rgb_to_gray, {})]
images_original = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images_original}
tensor_dict = preprocessor.preprocess(tensor_dict, preprocess_options)
images_gray = tensor_dict[fields.InputDataFields.image]
images_gray_r, images_gray_g, images_gray_b = tf.split(
value=images_gray, num_or_size_splits=3, axis=3)
images_r, images_g, images_b = tf.split(
value=images_original, num_or_size_splits=3, axis=3)
images_r_diff1 = tf.squared_difference(tf.to_float(images_r),
tf.to_float(images_gray_r))
images_r_diff2 = tf.squared_difference(tf.to_float(images_gray_r),
tf.to_float(images_gray_g))
images_r_diff = tf.multiply(images_r_diff1, images_r_diff2)
images_g_diff1 = tf.squared_difference(tf.to_float(images_g),
tf.to_float(images_gray_g))
images_g_diff2 = tf.squared_difference(tf.to_float(images_gray_g),
tf.to_float(images_gray_b))
images_g_diff = tf.multiply(images_g_diff1, images_g_diff2)
images_b_diff1 = tf.squared_difference(tf.to_float(images_b),
tf.to_float(images_gray_b))
images_b_diff2 = tf.squared_difference(tf.to_float(images_gray_b),
tf.to_float(images_gray_r))
images_b_diff = tf.multiply(images_b_diff1, images_b_diff2)
image_zero1 = tf.constant(0, dtype=tf.float32, shape=[1, 4, 4, 1])
with self.test_session() as sess:
(images_r_diff_, images_g_diff_, images_b_diff_, image_zero1_) = sess.run(
[images_r_diff, images_g_diff, images_b_diff, image_zero1])
self.assertAllClose(images_r_diff_, image_zero1_)
self.assertAllClose(images_g_diff_, image_zero1_)
self.assertAllClose(images_b_diff_, image_zero1_) 示例2: test_build_random_rgb_to_gray
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_rgb_to_gray [as 別名]
def test_build_random_rgb_to_gray(self):
preprocessor_text_proto = """
random_rgb_to_gray {
probability: 0.8
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.random_rgb_to_gray)
self.assert_dictionary_close(args, {'probability': 0.8}) 示例3: testRandomRGBtoGrayWithCache
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_rgb_to_gray [as 別名]
def testRandomRGBtoGrayWithCache(self):
preprocess_options = [(
preprocessor.random_rgb_to_gray, {'probability': 0.5})]
self._testPreprocessorCache(preprocess_options,
test_boxes=False,
test_masks=False,
test_keypoints=False) 示例4: testRandomCropImageWithCache
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_rgb_to_gray [as 別名]
def testRandomCropImageWithCache(self):
preprocess_options = [(preprocessor.random_rgb_to_gray,
{'probability': 0.5}),
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1,
}),
(preprocessor.random_crop_image, {})]
self._testPreprocessorCache(preprocess_options,
test_boxes=True,
test_masks=False,
test_keypoints=False)