add demo and OTB2015 test (200fps and 0.655AUC).

foolwood · Nov 29, 2018 · 14f07c9 · 14f07c9
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diff --git a/README.md b/README.md
@@ -20,8 +20,9 @@ Zheng Zhu<sup>\*</sup>, Qiang Wang<sup>\*</sup>, Bo Li<sup>\*</sup>, Wei Wu, Jun
 
 **DaSiamRPN** improves the performances of SiamRPN by (1) introducing an effective sampling strategy to control the imbalanced sample distribution, (2) designing a novel distractor-aware module to perform incremental learning, (3) making a long-term tracking extension. [ECCV2018](https://arxiv.org/pdf/1808.06048.pdf). (Slides at [VOT-18 Real-time challenge winners talk](https://drive.google.com/open?id=1dsEI2uYHDfELK0CW2xgv7R4QdCs6lwfr))
 
-<img src='votresult.png' width='800'>
-
+<div align="center">
+  <img src="votresult.png" width="700px" />
+</div>
 
 ## Prerequisites
 
@@ -58,6 +59,32 @@ All results can be downloaded from [Google Drive](https://drive.google.com/drive
 | <sub> **DaSiamRPN** </br> VOT2018 </sub> | <sub>-<sub> | <sub>-<sub>  | <sub>**0.59** / **0.28** / **0.383**<sub> | <sub>-<sub> | <sub>-<sub> | <sub>-<sub> |
 
 
+# Demo and Test OTB2015
+<div align="center">
+  <img src="code/data/bag.gif" width="400px" />
+</div>
+
+- To reproduce the reuslts on paper, the pretrained model can be downloaded from [Google Drive](https://drive.google.com/open?id=1BtIkp5pB6aqePQGlMb2_Z7bfPy6XEj6H): `SiamRPNOTB.model`. <br />
+:zap: :zap: This model is the **fastest**(~200fps) Siamese Tracker with AUC of 0.655 on OTB2015. :zap: :zap: 
+
+- You must download OTB2015 dataset (download [script](code/data/get_otb_data.sh)) at frist.
+
+A simple test example.
+
+```
+cd code
+python demo.py
+```
+
+If you want to test the performance on OTB2015, please using the follwing command.
+
+```
+cd code
+python test_otb.py
+python eval_otb.py OTB2015 "Siam*" 0 1
+```
+
+
 # License
 Licensed under an MIT license.
 

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diff --git a/code/data/OTB2015.json b/code/data/OTB2015.json
diff --git a/code/data/bag.gif b/code/data/bag.gif
diff --git a/code/data/get_otb_data.sh b/code/data/get_otb_data.sh
@@ -0,0 +1,10 @@
+#!/bin/bash
+# OTB2015
+mkdir OTB2015 && cd OTB2015
+baseurl="http://cvlab.hanyang.ac.kr/tracker_benchmark"
+wget "$baseurl/datasets.html"
+cat datasets.html | grep '\.zip' | sed -e 's/\.zip".*/.zip/' | sed -e s'/.*"//' >files.txt
+cat files.txt | xargs -n 1 -P 8 -I {} wget -c "$baseurl/{}"
+ls *.zip | xargs -n 1 unzip
+rm -r __MACOSX/
+cd ..
diff --git a/code/demo.py b/code/demo.py
@@ -0,0 +1,44 @@
+# --------------------------------------------------------
+# DaSiamRPN
+# Licensed under The MIT License
+# Written by Qiang Wang (wangqiang2015 at ia.ac.cn)
+# --------------------------------------------------------
+#!/usr/bin/python
+
+import glob, cv2, torch
+import numpy as np
+from os.path import realpath, dirname, join
+
+from net import SiamRPNvot
+from run_SiamRPN import SiamRPN_init, SiamRPN_track
+from utils import get_axis_aligned_bbox, cxy_wh_2_rect
+
+# load net
+net = SiamRPNvot()
+net.load_state_dict(torch.load(join(realpath(dirname(__file__)), 'SiamRPNVOT.model')))
+net.eval().cuda()
+
+# image and init box
+image_files = sorted(glob.glob('./bag/*.jpg'))
+init_rbox = [334.02,128.36,438.19,188.78,396.39,260.83,292.23,200.41]
+[cx, cy, w, h] = get_axis_aligned_bbox(init_rbox)
+
+# tracker init
+target_pos, target_sz = np.array([cx, cy]), np.array([w, h])
+im = cv2.imread(image_files[0])  # HxWxC
+state = SiamRPN_init(im, target_pos, target_sz, net)
+
+# tracking and visualization
+toc = 0
+for f, image_file in enumerate(image_files):
+    im = cv2.imread(image_file)
+    tic = cv2.getTickCount()
+    state = SiamRPN_track(state, im)  # track
+    toc += cv2.getTickCount()-tic
+    res = cxy_wh_2_rect(state['target_pos'], state['target_sz'])
+    res = [int(l) for l in res]
+    cv2.rectangle(im, (res[0], res[1]), (res[0] + res[2], res[1] + res[3]), (0, 255, 255), 3)
+    cv2.imshow('SiamRPN', im)
+    cv2.waitKey(1)
+
+print('Tracking Speed {:.1f}fps'.format((len(image_files)-1)/(toc/cv2.getTickFrequency())))