Update README.md

README.md

@@ -16,93 +16,16 @@ GEM is a multimodal LLM unifying ECG time series, 12-lead ECG images and text fo
 
 ## 🔥 Updates
 
+#### Project Page: 📖 [Page](https://www.lanxplanet.com/GEM-ECG/)
+
 #### Paper: 📄 [Arxiv](https://arxiv.org/pdf/2503.06073)
 
+#### Code: 💻 [GitHub](https://github.com/lanxiang1017/GEM)
+
 #### Model: 🤗 [GEM](https://huggingface.co/LANSG/GEM)
 
 #### Data: 🤗 [ECG-Grounding](https://huggingface.co/datasets/LANSG/ECG-Grounding)
 
-## Setup
-
-```shell
-git clone https://github.com/lanxiang1017/GEM.git
-bash GEM/setup.sh
-```
-
-## Data Preparation
-
-Please download required data:
-
-ECG:  
-- [MIMIC-IV](https://physionet.org/content/mimic-iv-ecg/1.0/)
-- [PTB-XL](https://physionet.org/content/ptb-xl/1.0.3/)
-- [Code-15%](https://zenodo.org/records/4916206)
-- [CPSC 2018](https://physionet.org/content/challenge-2020/1.0.2/training/cpsc_2018/)
-- [CSN](https://physionet.org/content/ecg-arrhythmia/1.0.0/)
-- [G12E](https://physionet.org/content/challenge-2020/1.0.2/training/georgia/)
-
-Images:
-- [ECG-Grounding-Images](https://huggingface.co/datasets/LANSG/ECG-Grounding) (mimic_gen)
-- [ECG-Bench](https://huggingface.co/datasets/PULSE-ECG/ECGBench)
-
-After downloading all of them, organize the data as follows in `./data`,
-
-```
-├── ecg_timeseries
-    └── champan-shaoxing
-    └── code15
-    └── cpsc2018
-    └── ptbxl
-    └── georgia
-    └── mimic-iv
-├── ecg_images
-    └── cod15_v4
-    └── csn_aug_all_layout_papersize
-    └── csn_ori_layout_papersize
-    └── csn_part_noise_layout_papersize
-    └── gen_images
-      └── mimic_gen
-    └── mimic
-    └── mimic_v4
-    └── ptb-xl
-├── ecg_bench
-    └── images
-    └── jsons
-├── ecg_jsons
-    └── ECG_Grounding_30k.json
-    └── ECG_Grounding_130k.json
-├── ecg_grounding_test_data
-    └── ecg-grounding-test.json
-
-```
-
-## Pretrained Model Preparation
-
-Pretrained ECG Encoder:
-  - [ECG-CoCa](https://github.com/YubaoZhao/ECG-Chat) : place it in ```GEM/ecg_coca/open_clip/checkpoint```
-
-Pretrained MLLMs:
-  - [PULSE](https://huggingface.co/PULSE-ECG/PULSE-7B)  
-  - [LLaVA](https://huggingface.co/liuhaotian/llava-v1.6-vicuna-7b)
-
-## Train
-
-```bash GEM/scripts/train_gem.sh```
-
-## Evaluation
-
-For ECG-Grounding:
-  - step 1. generate interpretations: ```GEM/evaluation/gem_bench/bench_ecggrounding.sh```
-  - step 2. process interpretations: ```GEM/gem_evaluation/process_gem_outputs.ipynb```
-  - step 3. generate GPT evaluation reports: ```GEM/gem_evaluation/generate_gpt_eval.py```
-  - step 4. process evaluation reports and get scores: ```GEM/gem_evaluation/process_grounding_scores.ipynb```
-
-For ECG-Bench:
-  - step 1. generate results: ```GEM/evaluation/gem_bench/bench_ecggrounding.sh```
-  - step 2. evaluate results: ```GEM/evaluation/evaluate_ecgbench.py```
-  - step 3. evaluate reports: ```GEM/evaluation/eval_report.py```
-
-*Note: You'll need to specify result paths first in all evaluation scripts*
 
 ## Citation
 
@@ -119,10 +42,3 @@ If you find GEM helpful for your research and applications, please cite our pape
       url={https://arxiv.org/abs/2503.06073}, 
 }
 ```
-
-## Acknowledgement
-We thank the authors of [PULSE](https://github.com/AIMedLab/PULSE/tree/dev) and [ECG-Chat](https://github.com/YubaoZhao/ECG-Chat) for their publicly released models, datasets, and training codes.
-
-## Code
-
-Code: https://github.com/lanxiang1017/GEM