Update README.md

README.md

@@ -30,4 +30,63 @@ task_categories:
 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))
+```