---
dataset_info:
  features:
  - name: rgb
    dtype: image
  - name: ir
    dtype: image
  splits:
  - name: train
    num_bytes: 743157232.6539416
    num_examples: 4113
  - name: test
    num_bytes: 186676141.08705837
    num_examples: 1029
  download_size: 928212503
  dataset_size: 929833373.7409999
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---

For modified FLIR 

Usage：
```py
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)

```