Datasets:
File size: 2,089 Bytes
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---
dataset_info:
features:
- name: image
dtype: image
- name: bounding_boxes
sequence:
sequence: float64
- name: classes
sequence: int64
splits:
- name: train
num_bytes: 147837671.888
num_examples: 2596
- name: validation
num_bytes: 26070707
num_examples: 458
download_size: 172845541
dataset_size: 173908378.888
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
license: apache-2.0
task_categories:
- image-classification
pretty_name: FLIR IR YOLO expansion
size_categories:
- 1K<n<10K
---
# FLIR IR YOLO expansion
Images from repository [FLIR_IR_Expansion](https://github.com/sensationTI/FLIR_IR_Expansion)
This expansion pack is prepared specifically for training a YOU-ONLY-LOOK-ONCE(YOLO) network. All frames are labeled in the YOLO format. If you want to use this expansion pack for other purposes, images are still available for download but requires manual labeling
## Download all dataset
If you want to download all dataset you must do
```
from datasets import load_dataset
dataset = load_dataset("SAE-AAI/FLIR_IR_Expansion")
```
If you only want to download `train` or `validation` split you must do
```
from datasets import load_dataset
train_dataset = load_dataset("SAE-AAI/FLIR_IR_Expansion", split='train')
validation_dataset = load_dataset("SAE-AAI/FLIR_IR_Expansion", split='validation')
```
## Download by stream
If you want to donwload dataset by stream, you must do
```
from datasets import load_dataset
iterable_dataset = load_dataset("SAE-AAI/FLIR_IR_Expansion", streaming=True)
```
now you can get every sample by
```
for sample in iterable_dataset['train']:
print(sample['bounding_boxes'], sample['classes'])
example['sample'].show()
break
```
or with
```
sample = next(iter(iterable_dataset['train']))
print(sample['bounding_boxes'], sample['classes'])
sample['image']
```
If you want to get a batch of samples you ca do
```
BS = 4
example_batch = list(iterable_dataset['train'].take(BS))
```
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