Usage

1. Environment Setup

Create the reproduction environment using the following command:

conda env create -f environment.yml

2. Data Preparation

Target Dataset

POPE (COCO split)

Put the dataset under /your_path/data and replace the placeholder in the code with your actual dataset path to ensure proper loading.

3. Usage Instructions

1. Navigate to the project directory:

cd ./OTT

2. Full-process inference commands (run sequentially):

# First inference script
bash run_pope.sh

# Second inference script
bash test_pope_my.sh

4. Key Notes

• This repository provides code for LLaVA-1.5 on the POPE COCO dataset

• Core logic of the proposed framework implemented in pope_fast.py.

• Follow the placeholders in the code to configure dataset paths and model loading parameters.

• This code draws heavily on the open-source work of PAI 、VISTA and MemVR, and we sincerely thank their contributions to the community.