Skip to content

GitLab

Commit e627d395 authored by drauh's avatar drauh
Browse files

Removing unecessary clipping in preprocessor.py (fix #2066)

parent 20a4313d
Show whitespace changes
Inline Side-by-side
Showing with 21 additions and 21 deletions
research/object_detection/core/preprocessor.py
View file @ e627d395
......@@ -726,7 +726,7 @@ def random_pixel_value_scale(image,
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
minval: lower ratio of scaling pixel values.
maxval: upper ratio of scaling pixel values.
seed: random seed.
......@@ -749,7 +749,7 @@ def random_pixel_value_scale(image,
preprocess_vars_cache)
image = tf.multiply(image, color_coef)
image = tf.clip_by_value(image, 0.0, 1.0)
image = tf.clip_by_value(image, 0.0, 255.0)
return image
......@@ -815,7 +815,7 @@ def random_rgb_to_gray(image,
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
probability: the probability of returning a grayscale image.
The probability should be a number between [0, 1].
seed: random seed.
......@@ -852,11 +852,11 @@ def random_adjust_brightness(image,
preprocess_vars_cache=None):
"""Randomly adjusts brightness.
Makes sure the output image is still between 0 and 1.
Makes sure the output image is still between 0 and 255.
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
max_delta: how much to change the brightness. A value between [0, 1).
seed: random seed.
preprocess_vars_cache: PreprocessorCache object that records previously
......@@ -876,8 +876,8 @@ def random_adjust_brightness(image,
preprocessor_cache.PreprocessorCache.ADJUST_BRIGHTNESS,
preprocess_vars_cache)
image = tf.image.adjust_brightness(image, delta)
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=1.0)
image = tf.image.adjust_brightness(image / 255, delta) * 255
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=255.0)
return image
......@@ -888,11 +888,11 @@ def random_adjust_contrast(image,
preprocess_vars_cache=None):
"""Randomly adjusts contrast.
Makes sure the output image is still between 0 and 1.
Makes sure the output image is still between 0 and 255.
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
min_delta: see max_delta.
max_delta: how much to change the contrast. Contrast will change with a
value between min_delta and max_delta. This value will be
......@@ -913,8 +913,8 @@ def random_adjust_contrast(image,
generator_func,
preprocessor_cache.PreprocessorCache.ADJUST_CONTRAST,
preprocess_vars_cache)
image = tf.image.adjust_contrast(image, contrast_factor)
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=1.0)
image = tf.image.adjust_contrast(image / 255, contrast_factor) * 255
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=255.0)
return image
......@@ -924,11 +924,11 @@ def random_adjust_hue(image,
preprocess_vars_cache=None):
"""Randomly adjusts hue.
Makes sure the output image is still between 0 and 1.
Makes sure the output image is still between 0 and 255.
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
max_delta: change hue randomly with a value between 0 and max_delta.
seed: random seed.
preprocess_vars_cache: PreprocessorCache object that records previously
......@@ -945,8 +945,8 @@ def random_adjust_hue(image,
delta = _get_or_create_preprocess_rand_vars(
generator_func, preprocessor_cache.PreprocessorCache.ADJUST_HUE,
preprocess_vars_cache)
image = tf.image.adjust_hue(image, delta)
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=1.0)
image = tf.image.adjust_hue(image / 255, delta) * 255
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=255.0)
return image
......@@ -957,11 +957,11 @@ def random_adjust_saturation(image,
preprocess_vars_cache=None):
"""Randomly adjusts saturation.
Makes sure the output image is still between 0 and 1.
Makes sure the output image is still between 0 and 255.
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
min_delta: see max_delta.
max_delta: how much to change the saturation. Saturation will change with a
value between min_delta and max_delta. This value will be
......@@ -982,8 +982,8 @@ def random_adjust_saturation(image,
generator_func,
preprocessor_cache.PreprocessorCache.ADJUST_SATURATION,
preprocess_vars_cache)
image = tf.image.adjust_saturation(image, saturation_factor)
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=1.0)
image = tf.image.adjust_saturation(image / 255, saturation_factor) * 255
image = tf.clip_by_value(image, clip_value_min=0.0, clip_value_max=255.0)
return image
......@@ -991,11 +991,11 @@ def random_distort_color(image, color_ordering=0, preprocess_vars_cache=None):
"""Randomly distorts color.
Randomly distorts color using a combination of brightness, hue, contrast
and saturation changes. Makes sure the output image is still between 0 and 1.
and saturation changes. Makes sure the output image is still between 0 and 255.
Args:
image: rank 3 float32 tensor contains 1 image -> [height, width, channels]
with pixel values varying between [0, 1].
with pixel values varying between [0, 255].
color_ordering: Python int, a type of distortion (valid values: 0, 1).
preprocess_vars_cache: PreprocessorCache object that records previously
performed augmentations. Updated in-place. If this
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment