# SPLT

**Repository Path**: lc790/SPLT

## Basic Information

- **Project Name**: SPLT
- **Description**: `Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-06-23
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# `Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking

![splt](https://github.com/iiau-tracker/SPLT/blob/master/results/SPLT.png)

### GOOD NEWS ! ! ! Our code has supported **python3.6**
Welcome to try(checkout to py36 branch) if you want to run our tracker with **python3.6**.

This is the official code for the ICCV 2019 paper[[arxiv]](https://arxiv.org/abs/1909.01840). This code has been tested on 
- RTX 2080Ti
- CUDA 10.0 + cuDNN 7.6 / CUDA 9.0 + cuDNN 7.1.2
- Python 2.7
- Ubuntu 18.04.2 LTS

Please cite our paper if you find it useful for your research.
```
@inproceedings{ iccv19_SPLT,
    title={`Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking},
    author={Yan, Bin and Zhao, Haojie and Wang, Dong and Lu, Huchuan and Yang, Xiaoyun},
    booktitle={IEEE International Conference on Computer Vision (ICCV)},
    year={2019}
}
```

## Installation

- Create anaconda environment:
```bash
conda create -n SPLT python=2.7
conda activate SPLT
```

- Clone the repo and install requirements:
```bash
git clone https://github.com/iiau-tracker/SPLT.git
cd <path/to/SPLT>
pip install -r requirements.txt
```

- CUDA and cuDNN:
```bash
conda install cudatoolkit=10.0
conda install cudnn=7.6.0

# or CUDA 9.0 + cuDNN 7.1.2 for TensorFlow  < 1.13.0
conda install cudatoolkit=9.0
conda install cudnn=7.1.2
```

## Models
| Model | Size | Google Drive  | Baidu |
|:-----:|:----:|:-------------:|:---------:|
| SiamRPN | 215 MB | [model.ckpt-470277](https://drive.google.com/open?id=1t-rJSHWGgm_9VfqzZaLfhN5XZ8dotXSb)  | [Mirror](https://pan.baidu.com/s/1Ft-OorgWQIh7rvWvdGodUA) |
| Verifier | 178 MB | [V_resnet50_VID_N-65624](https://drive.google.com/open?id=1jsGkEUinQwvotwWJzsMzXNaHOYkJrPeh)  | [Mirror](https://pan.baidu.com/s/1gHAaFAwgX5ROfaucaaGafQ) |
| Skimming | 24 MB | [Skim](https://drive.google.com/open?id=1b_Lo3tMtefFsQc7Er1VLqg_RDuig86w2)  | [Mirror](https://pan.baidu.com/s/15MxiizQAydPu0K9Nr9GPsg) |

- extract `model.ckpt-470277` to `./RPN`
- extract `V_resnet50_VID_N-65624` to `./Verifier`
- extract `Skim` to `./Skim`

## Demo
```bash
# modify 'PROJECT_PATH' in 'demo.py' 
python demo.py
```

## Evaluation on VOT
start from `RPN_Verifier_Skim_top3.py`

- modify `PROJECT_PATH` in `RPN_Verifier_Skim_top3.py`
- add `set_global_variable('python', 'env -i <path/to/anaconda/envs/SPLT/bin/python>');` to `configuration.m`

[raw resluts (vot-toolkt version 6.0.3)](https://github.com/iiau-tracker/SPLT/tree/master/results)

## Train
### Train the Verifier(optional)
Download [ResNet50](http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz) model pretrained on IMAGENET.Then put extracted ckpt file in train_Verifier/lib
```bash
cd train_Verifier/experiments
# modify paths in classify.py
python classify.py
# modify paths in triplet_pairs.py
python triplet_pairs.py
# modify paths in train_multi_gpu.py
python train_multi_gpu.py
```

### Train the Skimming(optional)
```bash
cd train_Skim
# modify paths in classify.py
python classify.py
# modify paths in skim_data.py
python skim_data.py
# modify paths in train_skim.py
python train_skim.py

```