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Configuration error
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import random
import torch
def short_size_scale(images, size):
h, w = images.shape[-2:]
short, long = (h, w) if h < w else (w, h)
scale = size / short
long_target = int(scale * long)
target_size = (size, long_target) if h < w else (long_target, size)
return torch.nn.functional.interpolate(
input=images, size=target_size, mode="bilinear", antialias=True
)
def random_short_side_scale(images, size_min, size_max):
size = random.randint(size_min, size_max)
return short_size_scale(images, size)
def random_crop(images, height, width):
image_h, image_w = images.shape[-2:]
h_start = random.randint(0, image_h - height)
w_start = random.randint(0, image_w - width)
return images[:, :, h_start : h_start + height, w_start : w_start + width]
def center_crop(images, height, width):
# offset_crop(images, 0,0, 200, 0)
image_h, image_w = images.shape[-2:]
h_start = (image_h - height) // 2
w_start = (image_w - width) // 2
return images[:, :, h_start : h_start + height, w_start : w_start + width]
def offset_crop(image, left=0, right=0, top=200, bottom=0):
n, c, h, w = image.shape
left = min(left, w-1)
right = min(right, w - left - 1)
top = min(top, h - 1)
bottom = min(bottom, h - top - 1)
image = image[:, :, top:h-bottom, left:w-right]
return image |