Omkar2118/datasets huggingface dataset:
RONIN
Full name: Robust Neural Inertial Navigation

## RoNIN

The RoNIN dataset contains over 40 hours of IMU sensor data from 100 human subjects with 3D ground-truth trajectories under natural human movements. This data set provides measurements of the accelerometer, gyroscope, magnetometer, and ground track, including direction and location in 327 sequences and at a frequency of 200 Hz. A two-device data collection protocol was developed. A harness was used to attach one phone to the body for 3D tracking, allowing subjects to control the other phone to collect IMU data freely. It should be noted that the ground track can only be obtained using the 3D tracker phone attached to the harness. In addition, the body trajectory is estimated instead of the IMU. RoNIN datset contians 42.7 hours of IMU-motion data over 276 sequences in 3 buildings, and collected from 100 human subjects with three Android devices. 


The dataset contains following:
<ol>
<li>Data 13.81 GB</li>
    <ul>seen_subjects_test_set.zip 3.15 GB </ul>
    <ul>train_dataset_1.zip 4.49 GB </ul>
    <ul>train_dataset_2.zip 3.18 GB </ul>
    <ul>unseen_subjects_test_set.zip 2.99 GB </ul>
    <br>
<li>Pretrained_Models 57.05 MB </li>
    <ul>ronin_body_heading.zip 579.52 KB </ul>
    <ul>ronin_lstm.zip 2.29 MB </ul>
    <ul>ronin_resnet.zip 48.49 MB </ul>
    <ul>ronin_tcn.zip 5.71 MB </ul>
</ol>

All HDF5 files are organized as follows

HDF5 data format
-----------------
<ol>
<li style="font-weight:bold">raw:</li>
     <ul style="font-weight:bold">tango:</ul>
     <ol><ul>gyro, gyro_uncalib, acce, magnet, game_rv, gravity, linacce, step, tango_pose, tango_adf_pose, rv, pressure, (optional) [wifi, gps, magnetic_rv, magnet_uncalib]</ul></ol>
     <ul style="font-weight:bold">imu:</ul>
        <ol><ul>gyro, gyro_uncalib, acce, magnet, game_rv, gravity, linacce, step. rv, pressure, (optional) [wifi, gps, magnetic_rv, magnet_uncalib]</ul></ol>
        <br>
<li style="font-weight:bold">synced:</li>
     <ul >time, gyro, gyro_uncalib, acce, magnet, game_rv, rv, gravity, linacce, step</ul>
     <br>
<li style="font-weight:bold">pose:</li>
     <ul>tango_pos, tango_ori, (optional) ekf_ori</ul>
     </ol>

Introducing paper: RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods
RepoIMU

## RepoIMU T-stick
 
The RepoIMU T-stick  is a small, low-cost, and high-performance inertial measurement unit (IMU) that can be used for a wide range of applications. The RepoIMU T-stick is a 9-axis IMU that measures the acceleration, angular velocity, and magnetic field. This database contains two separate sets of experiments recorded with a T-stick and a pendulum. A total of 29 trials were collected on the T-stick, and each trial lasted approximately 90 seconds. As the name suggests, the IMU is attached to a T-shaped stick equipped with six reflective markers. Each experiment consists of slow or fast rotation around a principal sensor axis or translation along a principal sensor axis. In this scenario, the data from the Vicon Nexus OMC system and the XSens MTi IMU are synchronized and provided at a frequency of 100 Hz. The authors clearly state that the IMU coordinate system and the ground trace are not aligned and propose a method to compensate for one of the two required rotations based on quaternion averaging. Unfortunately, some experiments contain gyroscope clipping and ground tracking, which significantly affect the obtained errors. Therefore, careful pre-processing and removal of some trials should be considered when using the dataset to evaluate the model's accuracy. 

## RepoIMU T-pendulum

The second part of the RepoIMU dataset contains data from a triple pendulum on which the IMUs are mounted. Measurement data is provided at 90 Hz or 166 Hz. However, the IMU data contains duplicate samples. This is usually the result of artificial sampling or transmission problems where missed samples are replaced by duplicating the last sample received, effectively reducing the sampling rate. The sampling rate achieved when discarding frequent samples is about 25 Hz and 48 Hz for the accelerometer and gyroscope, respectively. Due to this issue, it is not recommended to use this database for model training and evaluation. Due to this fact, we cannot recommend using pendulum tests to evaluate the accuracy of IOE with high precision.
MoB
Full name: Malicious or Benign Cartoon Videos

A dataset of cartoon video clips. For each video clip, the presence or absence of each feature was marked by the annotators. 

Malicious: Video  content  which may  not  be  suitable  for  viewing  by  toddlers  and  pre-schoolers includes a set of clearly defined, trivial and intu-itive features as well as some complex and subtle audio andvideo features. The former includes forms of obscenity and violence on a higher level e.g. nudity, gore, etc. while the latter includes elements such as fast repetitive motion, loud music, disgusting and scary characters, smashing people or things, forms of aggression, loud music, screaming or shout-ing, gunshots and explosions. 

Benign: Educational videos and videos of nursery rhymes are usually considered to be appropriate for the toddlers and pre-schoolers; in fact some experts recommend letting kids watch  them  for  a  limited  number  of  hours.Benign videos are characterized by a slower tempo, softer music or sound effects, moderate-paced motions, and soft-toned  conversations.  Most  importantly,  benign  video  content should not contain any indicators of malicious content as discussed earlier.

Introducing paper: Malicious or Benign? Towards Effective Content Moderation for Children's Videos