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Update README to remove outdated inference examples

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Removed sections on streaming inference from images and video, and updated example run command.
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Lin-Zhuo Chen
2026-04-21 13:59:21 +08:00
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@@ -130,30 +130,26 @@ python demo.py --model_path /path/to/lingbot-map-long.pt \
<img width="346" height="326" alt="output_pointcloud_cropped" src="https://github.com/user-attachments/assets/ae1eda30-70d6-4be6-87d1-b3206bee936c" /> <img width="346" height="326" alt="output_pointcloud_cropped" src="https://github.com/user-attachments/assets/ae1eda30-70d6-4be6-87d1-b3206bee936c" />
### Streaming Inference from Images
```bash
python demo.py --model_path /path/to/lingbot-map-long.pt \
--image_folder /path/to/images/
```
### Streaming Inference from Video
```bash
python demo.py --model_path /path/to/lingbot-map-long.pt \
--video_path video.mp4 --fps 10
```
We will provide more examples in the follow-up. We will provide more examples in the follow-up.
### Streaming with Keyframe Interval ### Streaming with Keyframe Interval
Use `--keyframe_interval` to reduce KV cache memory by only keeping every N-th frame as a keyframe. Non-keyframe frames still produce predictions but are not stored in the cache. This is useful for long sequences which exceed 320 frames (We train with video RoPE on 320 views, so performance degrades when the KV cache stores more than 320 views. Using a keyframe strategy allows inference over longer sequences.). Use `--keyframe_interval` to reduce KV cache memory by only keeping every N-th frame as a keyframe. Non-keyframe frames still produce predictions but are not stored in the cache. This is useful for long sequences which exceed 320 frames (We train with video RoPE on 320 views, so performance degrades when the KV cache stores more than 320 views. Using a keyframe strategy allows inference over longer sequences.).
**Dataset:** Download the demo sequences from [robbyant/lingbot-map-demo](https://huggingface.co/datasets/robbyant/lingbot-map-demo/tree/main) on Hugging Face.
Example run on the `travel` sequence from the dataset above (sky masking on, 4 camera optimization iterations, keyframe every 2 frames):
```bash ```bash
python demo.py --model_path /path/to/lingbot-map-long.pt \ python demo.py \
--image_folder /path/to/images/ --keyframe_interval 6 --image_folder /path/to/lingbot-map-demo/travel/ \
--model_path /path/to/lingbot-map-long.pt \
--mask_sky \
--camera_num_iterations 4 \
--keyframe_interval 2
``` ```
<img width="200" height="113" alt="output_pointcloud_original" src="https://github.com/user-attachments/assets/9670c821-09bf-45c5-9f1a-11d913b4a033" />
<img width="480" height="506" alt="output_pointcloud_cropped" src="https://github.com/user-attachments/assets/2d224204-1898-4d0d-b4f8-b8ae830e1d6c" />
### Windowed Inference (for long sequences, >3000 frames) ### Windowed Inference (for long sequences, >3000 frames)