Upload README.md

README.md

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+<div align="center">
+<h1> OmniCaptioner: One Captioner to Rule Them All </h1>
+
+</div>
+<div align="center">
+
+<p align="center">
+ <a href="https://alpha-innovator.github.io/OmniCaptioner-project-page/"><b>HomePage</b></a>&nbsp&nbsp | &nbsp&nbsp <a href="https://github.com/Alpha-Innovator/OmniCaptioner">Github</a>&nbsp&nbsp | &nbsp&nbsp <a href="https://huggingface.co/papers/2504.07089">Paper</a>&nbsp&nbsp
+</p>
+</div>
+
+
+## 💻 Finetuning Code
+### 1. Create a conda environment and install PyTorch
+```bash
+conda create -n OmniCap python=3.9
+conda activate OmniCap
+```
+### 2.Install dependencies
+```bash
+pip install -r requirements.txt
+```
+### 3. Install flash-attn
+```bash
+pip install flash-attn --no-build-isolation
+```
+### 4. Prepare data
+You can place the links to your data files in `./data/caption_data.yaml`.
+
+### 5. Start finetuning
+```bash
+bash scripts/finetune_caption_slurm.sh
+```
+## 🚀 Inference Code
+
+You can caption the image with AIGC style using the following command:
+
+
+```python   
+CUDA_VISIBLE_DEVICES=0 python src/inference_single_image.py \
+    --model_path your_model_path \
+    --image_path your_image_path  \
+    --image_type aigc 
+``` 
+
+You can caption the image with OCR style using the following command:
+
+```python   
+CUDA_VISIBLE_DEVICES=0 python src/inference_single_image.py \
+    --model_path your_model_path \
+    --image_path your_image_path  \
+    --image_type ocr 
+``` 
+## 🚀 Evaluation Code with LLM
+
+```python   
+
+cd VLMEvalkit
+conda create -n VLMEvalkit python=3.9
+conda activate VLMEvalkit
+pip install -e .
+
+CUDA_VISIBLE_DEVICES=0  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-qwen2-5-3B --verbose > output_omnicap_qwen2-5-3B_MMMU_DEV_VAL.log 2>&1 &
+CUDA_VISIBLE_DEVICES=0,1  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-qwen2-5-7B --verbose > output_omnicap_qwen2-5-7B_MMMU_DEV_VAL.log 2>&1 &
+CUDA_VISIBLE_DEVICES=0,1,2,3  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-qwen2-5-32B --verbose > output_omnicap_qwen2-5-32B_MMMU_DEV_VAL.log 2>&1 &
+
+CUDA_VISIBLE_DEVICES=0  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-deepseek-distill-7B --verbose > output_omnicap_deepseek_distill_3B_MMMU_DEV_VAL.log 2>&1 &
+CUDA_VISIBLE_DEVICES=0,1  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-deepseek-distill-32B --verbose > output_omnicap_deepseek_distill_32B_MMMU_DEV_VAL.log 2>&1 &
+CUDA_VISIBLE_DEVICES=0,1,2,3  nohup python run.py --data MMMU_DEV_VAL --model Omnicaptioner-deepseek-distill-70B --verbose > output_omnicap_deepseek_distill_70B_MMMU_DEV_VAL.log 2>&1 &
+
+``` 
+
+
+## Citation
+
+If you find the provided code or models useful for your research, consider citing them as:
+```
+
+```
+
+