git clone https://github.com/StrangerZhang/pysot-toolkit
pip install -r requirements.txt
cd pysot/utils/
python setup.py build_ext --inplace
# if you need to draw graph, you need latex installed on your system

cd /path/to/pysot-toolkit
python bin/eval.py \
	--dataset_dir /path/to/dataset/root \		# dataset path
	--dataset VOT2018 \				# dataset name(VOT2018, VOT2016)
	--tracker_result_dir /path/to/tracker/dir \	# tracker dir
	--trackers ECO UPDT SiamRPNpp 			# tracker names 

# you will see
------------------------------------------------------------
|Tracker Name| Accuracy | Robustness | Lost Number |  EAO  |
------------------------------------------------------------
| SiamRPNpp  |  0.600   |   0.234    |    50.0     | 0.415 |
|    UPDT    |  0.536   |   0.184    |    39.2     | 0.378 |
|    ECO     |  0.484   |   0.276    |    59.0     | 0.280 |
------------------------------------------------------------

cd /path/to/pysot-toolkit
python bin/eval.py \
	--dataset_dir /path/to/dataset/root \		# dataset path
	--dataset OTB100 \				# dataset name(OTB100, UAV123, NFS, LaSOT)
	--tracker_result_dir /path/to/tracker/dir \	# tracker dir
	--trackers SiamRPN++ C-COT DaSiamRPN ECO  \	# tracker names 
	--num 4 \				  	# evaluation thread
	--show_video_level \ 	  			# wether to show video results
	--vis 					  	# draw graph

# you will see (Normalized Precision not used in OTB evaluation)
-----------------------------------------------------
|Tracker name| Success | Norm Precision | Precision |
-----------------------------------------------------
| SiamRPN++  |  0.696  |     0.000      |   0.914   |
|    ECO     |  0.691  |     0.000      |   0.910   |
|   C-COT    |  0.671  |     0.000      |   0.898   |
| DaSiamRPN  |  0.658  |     0.000      |   0.880   |
-----------------------------------------------------

-----------------------------------------------------------------------------------------
|    Tracker name     |      SiamRPN++      |      DaSiamRPN      |         ECO         |
-----------------------------------------------------------------------------------------
|     Video name      | success | precision | success | precision | success | precision |
-----------------------------------------------------------------------------------------
|     Basketball      |  0.423  |   0.555   |  0.677  |   0.865   |  0.653  |   0.800   |
|        Biker        |  0.728  |   0.932   |  0.319  |   0.448   |  0.506  |   0.832   |
|        Bird1        |  0.207  |   0.360   |  0.274  |   0.508   |  0.192  |   0.302   |
|        Bird2        |  0.629  |   0.742   |  0.604  |   0.697   |  0.775  |   0.882   |
|      BlurBody       |  0.823  |   0.879   |  0.759  |   0.767   |  0.713  |   0.894   |
|      BlurCar1       |  0.803  |   0.917   |  0.837  |   0.895   |  0.851  |   0.934   |
|      BlurCar2       |  0.864  |   0.926   |  0.794  |   0.872   |  0.883  |   0.931   |
......
|        Vase         |  0.564  |   0.698   |  0.554  |   0.742   |  0.544  |   0.752   |
|       Walking       |  0.761  |   0.956   |  0.745  |   0.932   |  0.709  |   0.955   |
|      Walking2       |  0.362  |   0.476   |  0.263  |   0.371   |  0.793  |   0.941   |
|        Woman        |  0.615  |   0.908   |  0.648  |   0.887   |  0.771  |   0.936   |
-----------------------------------------------------------------------------------------

cd /path/to/pysot-toolkit
python bin/eval.py \
	--dataset_dir /path/to/dataset/root \		# dataset path
	--dataset VOT2018-LT \				# dataset name
	--tracker_result_dir /path/to/tracker/dir \	# tracker dir
	--trackers SiamRPN++ MBMD DaSiam-LT \		# tracker names 
	--num 4 \				  	# evaluation thread
	--vis \					  	# wether to draw graph

# you will see
-------------------------------------------
|Tracker Name| Precision | Recall |  F1   |
-------------------------------------------
| SiamRPN++  |   0.649   | 0.610  | 0.629 |
|    MBMD    |   0.634   | 0.588  | 0.610 |
| DaSiam-LT  |   0.627   | 0.588  | 0.607 |
|    MMLT    |   0.574   | 0.521  | 0.546 |
|  FuCoLoT   |   0.538   | 0.432  | 0.479 |
|  SiamVGG   |   0.552   | 0.393  | 0.459 |
|   SiamFC   |   0.600   | 0.334  | 0.429 |
-------------------------------------------

export PYTHONPATH=/path/to/pysot-toolkit:$PYTHONPATH

from pysot.datasets import DatasetFactory

dataset = DatasetFactory.create_dataset(name=dataset_name,
                                       	dataset_root=datset_root,
                                        load_img=False)
for video in dataset:
    for idx, (img, gt_bbox) in enumerate(video):
        if idx == 0:
            # init your tracker here
        else:
            # get tracking result here

from pysot.datasets import DatasetFactory
from pysot.utils.region import vot_overlap

dataset = DatasetFactory.create_dataset(name=dataset_name,
                                       	dataset_root=datset_root,
                                        load_img=False)
frame_counter = 0
pred_bboxes = []
for video in dataset:
    for idx, (img, gt_bbox) in enumerate(video):
        if idx == frame_counter:
            # init your tracker here
            pred_bbox.append(1)
        elif idx > frame_counter:
            # get tracking result here
            pred_bbox = 
            overlap = vot_overlap(pred_bbox, gt_bbox, (img.shape[1], img.shape[0]))
            if overlap > 0: 
	    	# continue tracking
                pred_bboxes.append(pred_bbox)
            else: 
	    	# lost target, restart
                pred_bboxes.append(2)
                frame_counter = idx + 5
        else:
            pred_bboxes.append(0)