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README.md

@@ -46,50 +46,4 @@ configs:
       - split: val
         path:
           - iGround_val_set_keys.jsonl
----
-
-## 📦 Loading the Dataset
-
-You can load each configuration and split directly with the 🤗 Datasets library:
-
-```python
-from datasets import load_dataset
-
-repo = "ekazakos/iGround"
-
-# Available configs:
-# - data_processed
-# - data_raw
-# - keys
-#
-# Each config includes the standard splits: train, val, and test.
-
-# data_processed: annotations after processing used to train GROVE.
-#   Processing merges multiple instances of the same object type in a clip
-#   into a single annotation by taking the union of all boxes for that instance.
-ds_proc_train = load_dataset(repo, "data_processed", split="train")
-ds_proc_val = load_dataset(repo, "data_processed", split="val")
-ds_proc_test = load_dataset(repo, "data_processed", split="test")
-
-# data_raw: raw annotations without any processing.
-#   The same object type can appear multiple times in a video,
-#   with distinct bounding boxes per instance and per frame.
-ds_raw_train = load_dataset(repo, "data_raw", split="train")
-ds_raw_val = load_dataset(repo, "data_raw", split="val")
-ds_raw_test = load_dataset(repo, "data_raw", split="test")
-
-# keys: contains the corresponding video_ids for the above splits.
-ds_keys_train = load_dataset(repo, "keys", split="train")
-ds_keys_val = load_dataset(repo, "keys", split="val")
-```
-
-If you use this dataset, please cite:
-
-```
-@article{kazakos2025grove,
-    title={Large-scale Pre-training for Grounded Video Caption Generation},
-    author={Evangelos Kazakos and Cordelia Schmid and Josef Sivic},
-    journal={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
-    year={2025}
-}
-```
+---

iGround_val_set_keys.jsonl

@@ -98,3 +98,403 @@
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