本文整理汇总了Python中imgaug.augmenters.MultiplyElementwise方法的典型用法代码示例。如果您正苦于以下问题：Python augmenters.MultiplyElementwise方法的具体用法？Python augmenters.MultiplyElementwise怎么用？Python augmenters.MultiplyElementwise使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类imgaug.augmenters的用法示例。
在下文中一共展示了augmenters.MultiplyElementwise方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: chapter_augmenters_multiplyelementwise
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MultiplyElementwise [as 别名]
def chapter_augmenters_multiplyelementwise():
aug = iaa.MultiplyElementwise((0.5, 1.5))
run_and_save_augseq(
"multiplyelementwise.jpg", aug,
[ia.quokka(size=(512, 512)) for _ in range(1)], cols=1, rows=1,
quality=90
)
aug = iaa.MultiplyElementwise((0.5, 1.5), per_channel=True)
run_and_save_augseq(
"multiplyelementwise_per_channel.jpg", aug,
[ia.quokka(size=(512, 512)) for _ in range(1)], cols=1, rows=1,
quality=90
) 示例2: __init__
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MultiplyElementwise [as 别名]
def __init__(self):
self.aug = A.MultiplicativeNoise((0, 1), per_channel=True, elementwise=True, p=1)
self.imgaug_transform = iaa.MultiplyElementwise(mul=(0, 1), per_channel=True) 示例3: main
# 需要导入模块: from imgaug import augmenters [as 别名]
# 或者: from imgaug.augmenters import MultiplyElementwise [as 别名]
def main():
args = parse_args()
package_versions = get_package_versions()
if args.print_package_versions:
print(package_versions)
images_per_second = defaultdict(dict)
libraries = args.libraries
data_dir = args.data_dir
paths = list(sorted(os.listdir(data_dir)))
paths = paths[: args.images]
imgs_cv2 = [read_img_cv2(os.path.join(data_dir, path)) for path in paths]
imgs_pillow = [read_img_pillow(os.path.join(data_dir, path)) for path in paths]
benchmarks = [
HorizontalFlip(),
VerticalFlip(),
Rotate(),
ShiftScaleRotate(),
Brightness(),
Contrast(),
BrightnessContrast(),
ShiftRGB(),
ShiftHSV(),
Gamma(),
Grayscale(),
RandomCrop64(),
PadToSize512(),
Resize512(),
RandomSizedCrop_64_512(),
Posterize(),
Solarize(),
Equalize(),
Multiply(),
MultiplyElementwise(),
]
for library in libraries:
imgs = imgs_pillow if library in ("torchvision", "augmentor", "pillow") else imgs_cv2
pbar = tqdm(total=len(benchmarks))
for benchmark in benchmarks:
pbar.set_description("Current benchmark: {} | {}".format(library, benchmark))
benchmark_images_per_second = None
if benchmark.is_supported_by(library):
timer = Timer(lambda: benchmark.run(library, imgs))
run_times = timer.repeat(number=1, repeat=args.runs)
benchmark_images_per_second = [1 / (run_time / args.images) for run_time in run_times]
images_per_second[library][str(benchmark)] = benchmark_images_per_second
pbar.update(1)
pbar.close()
pd.set_option("display.width", 1000)
df = pd.DataFrame.from_dict(images_per_second)
df = df.applymap(lambda r: format_results(r, args.show_std))
df = df[libraries]
augmentations = [str(i) for i in benchmarks]
df = df.reindex(augmentations)
if args.markdown:
makedown_generator = MarkdownGenerator(df, package_versions)
makedown_generator.print()
else:
print(df.head(len(augmentations)))