Webimport torch import os from torchvision import transforms from torchvision.transforms import functional as F import cv2 from PIL import Image import numpy as np from imgaug import augmenters as iaa import imgaug as ia import sys sys.path.append('..') from utils import get_label_info, one_hot_it # from utils import * import random Webimgaug.augmentables.segmaps Edit on GitHub imgaug.augmentables.segmaps ¶ Classes dealing with segmentation maps. E.g. masks, semantic or instance segmentation maps. imgaug.augmentables.segmaps.SegmentationMapOnImage(*args, **kwargs) [source] ¶ Deprecated. Use SegmentationMapsOnImage instead. (Note the plural ‘Maps’ instead …
augmenters.meta — imgaug 0.4.0 documentation - Read the Docs
WebStandard usage of these augmenters follows roughly the schema: import numpy as np import imgaug.augmenters as iaa aug = iaa.pillike.Affine(translate_px={"x": (-5, 5)}) image = np.full( (32, 32, 3), 255, dtype=np.uint8) images_aug = aug(images=[image, image, image]) Added in 0.4.0. WebMay 28, 2024 · from imgaug import augmenters as iaa I am getting the following error: File "tesing_imaug.py", line 1, in from imgaug import augmenters as iaa ImportError: … how to start borderlands 1 dlc
from imgaug import augmenters as iaa · Issue #801 · aleju/imgaug
WebJan 7, 2024 · import imageio import imgaug.augmenters import os from PIL import Image os.chdir ("C:\\Users\\name\\Desktop\\training\\JPEG") j = 0 gaussian_noise = imgaug.augmenters.AdditiveGaussianNoise (5, 10) for infile in os.listdir ("C:\\Users\\name\\Desktop\\training\\JPEG"): image = imageio.imread (infile) … Webmode=imgaug.ALL)), # # Execute 0 to 5 of the following (less important) augmenters per # image. Don't execute all of them, as that would often be way too # strong. # iaa.SomeOf((0, 5), [# Convert some images into their superpixel representation, # sample between 20 and 200 superpixels per image, but do # not replace all superpixels with their ... Webimport torch: import glob: import re: import matplotlib.pyplot as plt: import json: import pdb: import cv2: import torch.nn as nn: import argparse: import pydicom: from imgaug import augmenters as iaa: import imgaug as ia: import torch.nn.functional as F: import tensorflow as tf: tf.compat.v1.disable_eager_execution() from tensorflow import keras how to start bootcamp in windows