metadata
license: gpl-3.0
tags:
- tracking
- VOT
pretty_name: >-
TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the
Wild
size_categories:
- 10K<n<100K
TrackingNet devkit
Download from HuggingFace
Download splits
from huggingface_hub import snapshot_download
# Download TRAIN_0 split (90GB)
snapshot_download(repo_id="SilvioGiancola/TrackingNet",
repo_type="dataset", revision="main",
local_dir="TrackingNet_HF",
allow_patterns="*TRAIN_0/*")
# Download TEST split (35GB)
snapshot_download(repo_id="SilvioGiancola/TrackingNet",
repo_type="dataset", revision="main",
local_dir="TrackingNet_HF",
allow_patterns="*TEST/*")
# Download all TRAIN splits (1.2TB)
snapshot_download(repo_id="SilvioGiancola/TrackingNet",
repo_type="dataset", revision="main",
local_dir="TrackingNet_HF",
allow_patterns="*TRAIN*")
TrackingNet pip package
conda create -n TrackingNet python pip
pip install TrackingNet
Utility functions for TrackingNet
from TrackingNet.utils import getListSplit
# Get list of codenames for the 12 training + testing split
TrackingNetSplits = getListSplit()
print(getListSplit())
# returns ["TEST", "TRAIN_0", "TRAIN_1", "TRAIN_2", "TRAIN_3", "TRAIN_4", "TRAIN_5", "TRAIN_6", "TRAIN_7", "TRAIN_8", "TRAIN_9", "TRAIN_10", "TRAIN_11"]
# Get list of tracking sequences
print(getListSequence(split=TrackingNetSplits[1])) # return list of tracking sequences in that split
print(getListSequence(split="TEST")) # return list of tracking sequences for testing
print(getListSequence(split=["TRAIN_0", "TRAIN_1"])) # return list of tracking sequences for train splits 0 and 1
print(getListSequence(split="TRAIN")) # return list of tracking sequences for al train splits
Downloading TrackingNet
from TrackingNet.Downloader import TrackingNetDownloader
from TrackingNet.utils import getListSplit
downloader = TrackingNetDownloader(LocalDirectory="path/to/TrackingNet")
for split in getListSplit():
downloader.downloadSplit(split)