Python script to download the vot tracking datasets (tested on vot 2019 main, rgb-thermal dataset)

Python script to download the vot tracking datasets (tested on vot 2019 main, rgb-thermal dataset)

2020-08-05 20:33:19

Content:

• Approach to download vot-2019 dataset; 
• Approach to download vot-2019-rgbt dataset; 
• for the rgb-depth videos, or long-term videos, you can modify the code yourself to download them all. 
• Baiduyun links for vot-2019, vot-2019lt, vot-rgb-thermal dataset. 

 

Approach to download vot-2019 dataset; 

1. open this page: https://github.com/votchallenge/vot-toolkit/blob/master/stacks/stack_vot2019.m for the json file. 

2. wget http://data.votchallenge.net/vot2019/main/description.json 

3. execute the following python script. 

import json
import os
import wget,tarfile,zipfile
 
vot_2019_path = '/home/wangxiao/Documents/dataset/vot2019/'      # object file
json_path = '/home/wangxiao/Downloads/description.json'  # vot 2019 json file
anno_vot = 'vot2019'                           # vot2019 or vot2018 or vot2017
 
 
with open(json_path,'r') as fd:
    vot_2019 = json.load(fd)
home_page = vot_2019['homepage']
 
for i,sequence in enumerate(vot_2019['sequences']):
    print('download the {} sequences'.format(i+1))
    # 
    annotations = sequence['annotations']['url']
    data_url = sequence['channels']['color']['url'].split('../../')[-1]
 
    name = annotations.split('.')[0]
    file_name = annotations.split('.')[0] + '.zip'
 
    down_annotations = os.path.join(home_page,anno_vot,'main',annotations)
    down_data_url = os.path.join(home_page,data_url)
 
 
    image_output_name = os.path.join(vot_2019_path,name,'color',file_name)
    anno_output_name = os.path.join(vot_2019_path,name,file_name)
    out_dir = os.path.dirname(anno_output_name)
 
    if os.path.exists(out_dir) == False:
        os.mkdir(out_dir)
 
    # annotations download and unzip and remove it
    wget.download(down_annotations, anno_output_name)
    print('loading {} annotation'.format(name))
    # unzip
    file_zip = zipfile.ZipFile(anno_output_name,'r')
    for file in file_zip.namelist():
        file_zip.extract(file, out_dir)
        print('extract annotation {}/{}'.format(name,file))
    file_zip.close()
    os.remove(anno_output_name)
    print('remove annotation {}.zip'.format(name))
 
    # image download and unzip ad remove it
    out_dir = os.path.dirname(image_output_name)
    if os.path.exists(out_dir) == False:
        os.mkdir(out_dir)
    wget.download(down_data_url,image_output_name)
    print('loading {} sequence'.format(name))
 
    file_zip = zipfile.ZipFile(image_output_name,'r')
    for file  in file_zip.namelist():
        file_zip.extract(file,out_dir)
        print('extract image {}'.format(file))
    file_zip.close()
    os.remove(image_output_name)
    print('remove image file {}.zip'.format(name))
    print('sequence  {} Completed!'.format(i+1))

 

 

 

 

Approach to download vot-2019-rgb-thermal dataset; 

1. open this page: https://github.com/votchallenge/vot-toolkit/blob/master/stacks/stack_vot2019_rgbtir.m, and copy the link for the json file. 

2. wget http://data.votchallenge.net/vot2019/rgbtir/meta/description.json 

3. python download_vot2019_rgbt_dataet_script.py 

##################################################################################################
####　　　　　　　　　　   　Download the VOT2019-rgbt-thermal dataset
##################################################################################################


import json
import os
import wget,tarfile,zipfile
import pdb 
 
vot_2019_path = '/home/wangxiao/Documents/dataset/vot2019_rgbt_dataset/'      # object file
json_path = '/home/wangxiao/Downloads/description_rgbt.json'  # vot 2019 json file
anno_vot = 'vot2019'                           # vot2019 or vot2018 or vot2017
 
 
with open(json_path,'r') as fd:
    vot_2019 = json.load(fd)
home_page = vot_2019['homepage']
 
for i,sequence in enumerate(vot_2019['sequences']):
    print('download the {} sequences'.format(i+1))
    # 
    annotations = sequence['annotations']['url']
    rgb_data_url = sequence['channels']['color']['url'].split('../')[-1]  
    ir_data_url = sequence['channels']['ir']['url'].split('../')[-1]  

 
    name = annotations.split('.')[0]
    file_name = annotations.split('.')[0] + '.zip'
 
    down_annotations = os.path.join(home_page, anno_vot,'rgbtir/meta', annotations)
    down_rgb_data_url = os.path.join(home_page, anno_vot, 'rgbtir', rgb_data_url)
    down_ir_data_url = os.path.join(home_page, anno_vot, 'rgbtir', ir_data_url)
 
 
    rgb_image_output_name = os.path.join(vot_2019_path, name, 'color', file_name)
    ir_image_output_name = os.path.join(vot_2019_path, name, 'ir', file_name)

    anno_output_name = os.path.join(vot_2019_path, name, file_name)
    out_dir = os.path.dirname(anno_output_name)
 
    if os.path.exists(out_dir) == False:
        os.mkdir(out_dir)

    # pdb.set_trace() 

    ###########################################################################
    ####            Download Annotation files 
    ###########################################################################    
    # annotations download and unzip and remove it
    wget.download(down_annotations, anno_output_name)
    print('loading {} annotation'.format(name))
    # unzip
    file_zip = zipfile.ZipFile(anno_output_name,'r')
    for file in file_zip.namelist():
        file_zip.extract(file, out_dir)
        print('extract annotation {}/{}'.format(name,file))
    file_zip.close()
    os.remove(anno_output_name)
    print('remove annotation {}.zip'.format(name))
 

    ###########################################################################
    ####            Download Color images 
    ###########################################################################    
    # image download and unzip ad remove it
    out_dir = os.path.dirname(rgb_image_output_name)
    if os.path.exists(out_dir) == False:
        os.mkdir(out_dir)

    # pdb.set_trace()
    wget.download(down_rgb_data_url, rgb_image_output_name)
    print('loading {} sequence --- rgb files ...'.format(name))
 
    file_zip = zipfile.ZipFile(rgb_image_output_name,'r')
    for file  in file_zip.namelist():
        file_zip.extract(file,out_dir)
        print('extract image {}'.format(file))
    file_zip.close()
    os.remove(rgb_image_output_name)
    print('remove image file {}.zip'.format(name))
    print('sequence  {} Completed!'.format(i+1))

    ###########################################################################
    ####            Download Infrared images 
    ###########################################################################    
    # image download and unzip ad remove it
    out_dir = os.path.dirname(ir_image_output_name)
    if os.path.exists(out_dir) == False:
        os.mkdir(out_dir)

    # pdb.set_trace()
    wget.download(down_ir_data_url, ir_image_output_name)
    print('loading {} sequence --- infrared files ...'.format(name))
    
    file_zip = zipfile.ZipFile(ir_image_output_name, 'r')
    for file  in file_zip.namelist():
        file_zip.extract(file,out_dir)
        print('extract image {}'.format(file))
    file_zip.close()
    os.remove(ir_image_output_name)
    print('remove image file {}.zip'.format(name))
    print('sequence  {} Completed!'.format(i+1))



print("=====================================================================")
print("             Great!!! All videos have been dowloaded ......")
print("=====================================================================")

4. Then, you can download videos automatically. 

 

 

 

 

 

 

====>> If you just want the dataset, well, I have downloaded all the videos and uploaded them into the Baiduyun drive. You can take it away, and No Thanks! 

Baiduyun disk: 

vot 2018 and vot 2019: 　   链接: https://pan.baidu.com/s/1q6lv3cUhezBb5pmdj3BRGw 提取码: d7r3 

vot 2018 LT: 　　　　　　链接: https://pan.baidu.com/s/16Q4_sxhBjmddIHU8b7XK3w 提取码: 67xf 

vot 2019 LT: 　　　　　　链接：https://pan.baidu.com/s/1z9HBPNprbt2gb2RGzRJkwA  提取码：7yq5

vot 2019 rgb-thermal: 　　链接: https://pan.baidu.com/s/1oT8qFmKBpYa3VlXP1ZwfCA 提取码: mn1b

 

Reference: 

1. csdn blog