Update docs/CLI_USAGE.md
This commit is contained in:
+14
-1
@@ -53,9 +53,11 @@ We provide <a href="https://github.com/Stability-AI/stable-virtual-camera/releas
|
||||
└── scene_3
|
||||
```
|
||||
|
||||
You can specify which scene to run by passing in `--data_items scene_1 scene_2` to run, for example, `scene_1` and `scene_2`.
|
||||
|
||||
### Recommended Usage
|
||||
|
||||
- `img2img` and `img2vid` are recommended to be used for evaluation and benchmarking. These two tasks are used for the quantitative evalution throught the <a href="http://arxiv.org/abs/2503.14489">paper</a>. The data is converted from academic datasets so the groundtruth target views are available for metric computation. Check the [`benchmark`](../benchmark/) folder for detailed splits we organize to benchmark different NVS models.
|
||||
- `img2img` and `img2vid` are recommended to be used for evaluation and benchmarking. These two tasks are used for the quantitative evalution in our <a href="http://arxiv.org/abs/2503.14489">paper</a>. The data is converted from academic datasets so the groundtruth target views are available for metric computation. Check the [`benchmark`](../benchmark/) folder for detailed splits we organize to benchmark different NVS models.
|
||||
- `img2vid` requries both the input and target views to be sorted, which is usually not guaranteed in general usage.
|
||||
- `img2trajvid_s-prob` is for general usage but only for single-view regime and fixed preset camera control.
|
||||
- `img2trajvid` is the task designed for general usage since it does not need the ordering of the input views. This is the task used in the gradio demo.
|
||||
@@ -78,6 +80,17 @@ python demo.py \
|
||||
- For the evaluation in semi-dense-view regime (i.e., DL3DV-140 and Tanks and Temples dataset) with `32` input views, we zero-shot extend `T` to fit all input and target views in one forward. Specifically, we set `--T 90` for the DL3DV-140 dataset and `--T 80` for the Tanks and Temples dataset.
|
||||
- For the evaluation on ViewCrafter split (including the RealEastate10K, CO3D, and Tanks and Temples dataset), we find zero-shot extending `T` to `25` to fit all input and target views in one forward is better. Also, the V split uses the original image resolutions: we therefore set `--T 25 --L_short 576`.
|
||||
|
||||
For example, you can run the following command on the example `dl3d140-165f5af8bfe32f70595a1c9393a6e442acf7af019998275144f605b89a306557` with 1 input view:
|
||||
|
||||
```bash
|
||||
python demo.py \
|
||||
--data_path /path/to/assets_demo_cli/ \
|
||||
--data_items dl3d140-165f5af8bfe32f70595a1c9393a6e442acf7af019998275144f605b89a306557 \
|
||||
--num_inputs 1 \
|
||||
--chunk_strategy nearest-gt \
|
||||
--video_save_fps 10
|
||||
```
|
||||
|
||||
## `img2vid`
|
||||
|
||||
```bash
|
||||
|
||||
Reference in New Issue
Block a user