│
├── datasets/ # folder with all of the data used for training and scripts for loading it on server
│   └── custom_dataset/ # folder with our special custom dataset
│   │   ├── base/ # folder with final parquets used for first pre train stage (only captions)
│   │   ├── fine_tune/ # folder with final parquets used for second finetune stage (various RS tasks)
│   │   ├── dataset_gather/ # folder with scripts used for gathering our custom dataset
│   │   └── data_EDA.ipynb # notebook with different statistics, hypothesis checking scripts and etc.
│   └── vhm_dataset/ # folder with original dataset configured by https://github.com/opendatalab
│
├── eval/ # folder with all files used to evaluate models
│   ├── eval_kits/ # various opensource benchmarks used to evaluate our trained models
│   │   ├── RSEvalKit/ # eval kit 1, special thank to authors for their contribution -> https://github.com/fitzpchao/RSEvalKit/tree/master?tab=readme-ov-file
│   │   └── ScoreRS/ # eval kit 2, special thank to authors for their contribution -> https://github.com/NJU-LHRS/ScoreRS/tree/main
│   │       ├── python_script/ # main folder with scripts to run model inferences
│   │       ├── eval_data/ # folder with datasets used in this benchmarks
│   │       ├── eval_launches/ # folder with bash files to launch model inferencing
│   │       └── ... # other scripts used by ScoreRS
│   └── eval_results/
│       ├── model_evaluator/ # folder with streamlit app and notebooks used to build leaderboard and compare models
│       │   ├── get_all_model_profiles.ipynb # notebook with simple scripts to get the benchmarks results of all tested models
│       │   └── leaderboard.py # script to launch streamlit app to view testing results
│       ├── score_rs_eval_results/ # folder with results of inferencing models on eval kit 1 (RSEvalKit)
│       └── rsevalkit_eval_results/ # folder with results of inferencing models on eval kit 2 (ScoreRS)
│
├── models/ # different models architectures used and developed
│   ├── VHM/ # base of this model was taken from this repository -> https://github.com/opendatalab/VHM, special thanks to the authors
│   │    ├── scipts/ # folder with bash scripts to launch training processes + deepspeed configurations
│   │    │   ├── rs/ # folder with bash scripts to launch training processes
│   │    │   └── zero2.json | zero3_offload.json | zero3.json | # deepspeed configurations
│   │    ├── trained_models/ # folder with trained models weights and configurations
│   │    └── vhm/ # main model folder
│   │        ├── model/ # folder with architecture designed by https://github.com/opendatalab
│   │        ├── train/ # scripts to train VHM based models\
│   │        │   ├── train.py # original vhm training script with llama attention
│   │        │   ├── train_mem.py # original vhm training with flash attention
│   │        │   ├── train_custom_dataset.py # custom training script for vhm based models with llama attention
│   │        │   ├── train_custom_dataset_flash_attention.py # custom training script for vhm based models with flash attention
│   │        │   └── ... # other scripts
│   │        └── ... # other utils
│   ├── VHM_W_Q_FORMER/ # custom arhitecture
│   │    ├── scipts/ # folder with bash scripts to launch training processes + deepspeed configurations
│   │    │   ├── rs/ # folder with bash scripts to launch training processes
│   │    │   └── zero2.json | zero3_offload.json | zero3.json | # deepspeed configurations
│   │    ├── trained_models/ # folder with trained models weights and configurations
│   │    └── vhm_w_q_former/ # main model folder
│   │        ├── model/ # folder with architecture designed by us
│   │        ├── train/ # scripts to train models\
│   │        │   ├── train.py # training script with llama attention
│   │        │   ├── train_mem.py # training with flash attention
│   │        │   ├── train_custom_dataset.py # custom training script for q-former models with llama attention
│   │        │   ├── train_custom_dataset_flash_attention.py # custom training script for q-former models with flash attention
│   │        │   └── ... # other scripts
│   │        └── ... # other utils
│   ├── VHM_W_Q_FORMER_V2/ # custom arhitecture
│   │    ├── scipts/ # folder with bash scripts to launch training processes + deepspeed configurations
│   │    │   ├── rs/ # folder with bash scripts to launch training processes
│   │    │   └── zero2.json | zero3_offload.json | zero3.json | # deepspeed configurations
│   │    ├── trained_models/ # folder with trained models weights and configurations
│   │    └── vhm_w_q_former/ # main model folder
│   │        ├── model/ # folder with architecture designed by us
│   │        ├── train/ # scripts to train VHM based models\
│   │        │   ├── train.py # custom training script with llama attention
│   │        │   ├── train_mem.py # training with flash attention
│   │        │   ├── train_custom_dataset.py # custom training script for models with q-former
│   │        │   ├── train_custom_dataset_flash_attention.py # custom training script for q-former models with flash attention
│   │        │   └── ... # other scripts
│   │        └── ... # other utils
│   ├── VHM_W_QWEN/ # custom arhitecture
│   │    ├── scipts/ # folder with bash scripts to launch training processes + deepspeed configurations
│   │    │   ├── rs/ # folder with bash scripts to launch training processes
│   │    │   └── zero2.json | zero3_offload.json | zero3.json | # deepspeed configurations
│   │    ├── trained_models/ # folder with trained models weights and configurations
│   │    └── vhm_w_qwen/ # main model folder
│   │        ├── model/ # folder with architecture designed by us
│   │        ├── train/ # scripts to train VHM based models\
│   │        │   ├── train.py # custom training script with qwen
│   │        │   ├── train_mem.py # training with flash attention
│   │        │   ├── train_custom_dataset.py # custom training script for qwen models
│   │        │   ├── train_custom_dataset_flash_attention.py # custom training script for qwen models with flash attention
│   │        │   └── ... # other scripts
│   └──      └── ... # other utils
└── README.md