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import albumentations as A | |
import cv2 | |
import torch | |
from albumentations.pytorch import ToTensorV2 | |
DEVICE = "cuda" if torch.cuda.is_available() else "cpu" | |
IMAGE_SIZE = 416 | |
transforms = A.Compose( | |
[ | |
A.LongestMaxSize(max_size=IMAGE_SIZE), | |
A.PadIfNeeded( | |
min_height=IMAGE_SIZE, min_width=IMAGE_SIZE, border_mode=cv2.BORDER_CONSTANT | |
), | |
A.Normalize(mean=[0, 0, 0], std=[1, 1, 1], max_pixel_value=255,), | |
ToTensorV2(), | |
], | |
) | |
ANCHORS = [ | |
[(0.28, 0.22), (0.38, 0.48), (0.9, 0.78)], | |
[(0.07, 0.15), (0.15, 0.11), (0.14, 0.29)], | |
[(0.02, 0.03), (0.04, 0.07), (0.08, 0.06)], | |
] # Note these have been rescaled to be between [0, 1] | |
S = [IMAGE_SIZE // 32, IMAGE_SIZE // 16, IMAGE_SIZE // 8] | |
PASCAL_CLASSES = [ | |
"aeroplane", | |
"bicycle", | |
"bird", | |
"boat", | |
"bottle", | |
"bus", | |
"car", | |
"cat", | |
"chair", | |
"cow", | |
"diningtable", | |
"dog", | |
"horse", | |
"motorbike", | |
"person", | |
"pottedplant", | |
"sheep", | |
"sofa", | |
"train", | |
"tvmonitor" | |
] | |