File size: 4,998 Bytes
33569f9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | # Dataset Preparation
## Training data
- annotation: We place the annotation file in [dataset/trainval/train_2k5.json](../dataset/trainval/train_2k5.json).
- original videos: You can download download from our organized version in [Boshenxx/TimeR1-Dataset](https://huggingface.co/datasets/Boshenxx/TimeR1-Dataset);
or you can download and organize the original data from [VTG-IT](https://huggingface.co/datasets/Yongxin-Guo/VTG-IT), [TimeIT](https://huggingface.co/datasets/ShuhuaiRen/TimeIT), [TimePro](https://huggingface.co/Lanxingxuan/TimeSuite), [HTStep](https://openreview.net/pdf?id=vv3cocNsEK) and [LongVid](https://huggingface.co/datasets/OpenGVLab/LongVid).
## Testing data
folder structure:
```
dataset
├─ timer1
│ ├─ annotations
│ │ ├─ train_2k5.json
│ │ └─ tvgbench.json
│ ├─ videos
│ │ ├─ timerft_data
│ │ | ├─ xxx.mp4
│ │ │ └─ ...
│ │ ├─ tvgbench_data
│ │ | ├─ xxx.mp4
│ │ │ └─ ...
├─ activitynet
│ ├─ annotations
│ │ ├─ sentence_temporal_grounding
│ │ │ └─ test.json
│ ├─ videos
│ | ├─ v_zzz_3yWpTXo.mp4
│ │ └─ ...
├─ charades
│ ├─ Charades_anno
│ │ └─ Charades_v1_test.csv
│ ├─ Charades_v1
│ | ├─ 0I0FX.mp4
│ │ └─ ...
├─ mvbench
│ ├─ json
│ │ ├─ action_antonym.json
│ │ └─ ...
│ ├─ videos
│ │ ├─ clevrer
│ │ └─ ...
├─ tempcompass
│ ├─ questions
│ │ ├─ multi-choice.json
│ │ └─ ...
│ ├─ videos
│ │ ├─ 315784.mp4
│ │ └─ ...
├─ egoschema
│ ├─ MC
│ │ └─ test-00000-of-00001.parquet
│ ├─ Subset
│ │ └─ test-00000-of-00001.parquet
│ ├─ videos
│ │ ├─ 001934bb-81bd-4cd8-a574-0472ef3f6678.mp4
│ │ └─ ...
├─ videomme
│ ├─ videomme
│ │ └─ test-00000-of-00001.parquet
│ ├─ data
│ │ ├─ _8lBR0E_Tx8.mp4
└─ └─ └─ ...
```
### ActivityNet
Download link: [ActivityNet](https://cs.stanford.edu/people/ranjaykrishna/densevid/)
For fine-tuning setting, before training, you need to preprocess the video data.
```bash
bash preprocess_video.sh
```
Specify the path to the Charades-STA dataset (video files, annotations, etc.).
### Charades
Download link: [Charades-v1](https://huggingface.co/datasets/HuggingFaceM4/charades)
For fine-tuning setting, before training, you need to preprocess the video data.
```bash
bash preprocess_video.sh
```
Specify the path to the Charades-STA dataset (video files, annotations, etc.).
### TVGBench
Download link: [hf: Boshenxx/TimeR1-Dataset](https://huggingface.co/datasets/Boshenxx/TimeR1-Dataset)
### MVBench
We place the annotation file of tvgbench in [dataset/trainval/tvgbench.json](../dataset/trainval/tvgbench.json).
Download link: [hf: OpenGVLab/MVBench](https://huggingface.co/datasets/OpenGVLab/MVBench)
### VideoMME
Download link: [hf: lmms-lab/MVBench](https://huggingface.co/datasets/lmms-lab/Video-MME)
### Egoschema
Download link: [hf: lmms-lab/egoschema](https://huggingface.co/datasets/lmms-lab/egoschema)
### TempCompass
Download link: [hf: lmms-lab/TempCompass](https://huggingface.co/datasets/lmms-lab/TempCompass)
|