Release new model and fix some issues:

1. Release layout conditioned CTSD 3.5 config, checkpoint, example.
2. Fix bugs about S3FS list (>1k items), DiT pointwise temporal attention.
3. Allow to config BEV condition drawing by solid shape or outline.

Author: wzhgba

README.md

@@ -1,11 +1,9 @@
 # Open Driving World Models (OpenDWM)
 
-[[中文简介](README_intro_zh.md)]
+[![Youtube](https://badges.aleen42.com/src/youtube.svg)](https://youtu.be/j9RRj-xzOA4) [<img src=https://img.shields.io/badge/%E4%B8%AD%E6%96%87%E7%AE%80%E4%BB%8B-blue>](README_intro_zh.md) 
 
 https://github.com/user-attachments/assets/649d3b81-3b1f-44f9-9f51-4d1ed7756476
 
-[Video link](https://youtu.be/j9RRj-xzOA4)
-
 Welcome to the OpenDWM project! This is an open-source initiative, focusing on autonomous driving video generation. Our mission is to provide a high-quality, controllable tool for generating autonomous driving videos using the latest technology. We aim to build a codebase that is both user-friendly and highly reusable, and hope to continuously improve the project through the collective wisdom of the community.
 
 The driving world models generate multi-view images or videos of autonomous driving scenes based on text and road environment layout conditions. Whether it's the environment, weather conditions, vehicle type, or driving path, you can adjust them according to your needs.
@@ -49,6 +47,7 @@ python -m pip install torch==2.5.1 torchvision==0.20.1
 ```
 
 Clone the repository, then install the dependencies.
+
 ```
 cd DWM
 git submodule update --init --recursive
@@ -62,27 +61,27 @@ Our cross-view temporal SD (CTSD) pipeline support loading the pretrained SD 2.1
 | Base model | Text conditioned <br/> driving generation | Text and layout (box, map) <br/> conditioned driving generation |
 | :-: | :-: | :-: |
 | [SD 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1) | [Config](configs/ctsd/multi_datasets/ctsd_21_tirda_nwao.json), [Download](http://103.237.29.236:10030/ctsd_21_tirda_nwao_30k.pth) | [Config](configs/ctsd/multi_datasets/ctsd_21_tirda_bm_nwa.json), [Download](http://103.237.29.236:10030/ctsd_21_tirda_bm_nwa_30k.pth) |
-| [SD 3.0](https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers) | | [UniMLVG Config](configs/ctsd/unimlvg/unimlvg_stage3_tirda_nwa.json), [Download](http://103.237.29.236:10030/ctsd_unimlvg_tirda_bm_nwa_60k.pth) |
-| [SD 3.5](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium) | [Config](configs/ctsd/multi_datasets/ctsd_35_tirda_nwao.json), [Download](http://103.237.29.236:10030/ctsd_35_tirda_nwao_20k.pth) | [Config](configs/ctsd/multi_datasets/ctsd_35_tirda_bm_nwa.json), Released by 2025-3-1 |
+| [SD 3.0](https://huggingface.co/stabilityai/stable-diffusion-3-medium-diffusers) | | [UniMLVG Config](configs/ctsd/unimlvg/ctsd_unimlvg_stage3_tirda_bm_nwa.json), [Download](http://103.237.29.236:10030/ctsd_unimlvg_tirda_bm_nwa_60k.pth) |
+| [SD 3.5](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium) | [Config](configs/ctsd/multi_datasets/ctsd_35_tirda_nwao.json), [Download](http://103.237.29.236:10030/ctsd_35_tirda_nwao_20k.pth) | [Config](configs/ctsd/multi_datasets/ctsd_35_tirda_bm_nwao.json), [Download](http://103.237.29.236:10030/ctsd_35_tirda_bm_nwao_40k.pth) |
 
 ## Examples
 
 ### T2I, T2V generation with CTSD pipeline
 
 Download base model (for VAE, text encoders, scheduler config) and driving generation model checkpoint, and edit the [path](examples/ctsd_35_6views_image_generation.json#L102) and [prompts](examples/ctsd_35_6views_image_generation.json#L221) in the JSON config, then run this command.
 
-```
+```bash
 PYTHONPATH=src python examples/ctsd_generation_example.py -c examples/ctsd_35_6views_image_generation.json -o output/ctsd_35_6views_image_generation
 ```
 
 ### Layout conditioned T2V generation with CTSD pipeline
 
-1. Download base model (for VAE, text encoders, scheduler config) and driving generation model checkpoint, and edit the [path](examples/ctsd_21_6views_video_generation_with_layout.json#L119) in the JSON config.
-2. Download layout resource package [nuscenes_scene-0627_package.zip](http://103.237.29.236:10030/nuscenes_scene-0627_package.zip) and unzip to the `{RESOURCE_PATH}`. Then edit the meta [path](examples/ctsd_21_6views_video_generation_with_layout.json#L129) as `{RESOURCE_PATH}/data.json` in the JSON config.
+1. Download base model (for VAE, text encoders, scheduler config) and driving generation model checkpoint, and edit the [path](examples/ctsd_35_6views_video_generation_with_layout.json#L156) in the JSON config.
+2. Download layout resource package ([nuscenes_scene-0627_package.zip](http://103.237.29.236:10030/nuscenes_scene-0627_package.zip), or [carla_town04_package](http://103.237.29.236:10030/carla_town04_package.zip)) and unzip to the `{RESOURCE_PATH}`. Then edit the meta [path](examples/ctsd_35_6views_video_generation_with_layout.json#L162) as `{RESOURCE_PATH}/data.json` in the JSON config.
 3. Run this command to generate the video.
 
-```
-PYTHONPATH=src python src/dwm/preview.py -c examples/ctsd_unimlvg_6views_video_generation.json -o output/ctsd_unimlvg_6views_video_generation
+```bash
+PYTHONPATH=src python src/dwm/preview.py -c examples/ctsd_35_6views_video_generation_with_layout.json -o output/ctsd_35_6views_video_generation_with_layout
 ```
 
 ## Train