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For modified FLIR
Usage:
from torchvision import transforms
from datasets import load_dataset
dataset_name = "newguyme/flir_paired"
dataset_flir_paired = load_dataset(dataset_name, split="train",use_auth_token=True)
# dataset_flir_paired
flir_preprocess = transforms.Compose(
[
transforms.Resize((config.image_size, config.image_size)),
# transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.5], [0.5]),
]
)
def flir_transform(examples):
rgb = [flir_preprocess(image.convert("RGB")) for image in examples["rgb"]]
ir = [flir_preprocess(image.convert("RGB")) for image in examples["ir"]]
return {"rgb_t_3ch": rgb, "ir_t_3ch":ir}
dataset_flir_paired.set_transform(flir_transform)
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