marc-tonsen

This script extends blink, fixation and gaze data by adding an additional column "world_frame_index" to every CSV file. This column indicates the closest available world video frame for each data sample.

To install the dependencies, run the following

pip install numpy pandas

Before executing the file, customize the file paths in the beginning of the file. If you do not want one of the files to be edited, e.g. the fixations file, then set the according path to "None", i.e. fixations_path = None.

marc-tonsen

import av
import cv2
import json
import struct
import pathlib
import argparse
import requests
import itertools
import numpy as np
from tqdm import tqdm

marc-tonsen

Scanpath Visualization

This Python script reads the Pupil Cloud raw data export and renders the subject's scanpath into the scene video.

Installation

1. To install the requirements run pip install more_itertools pandas numpy tqdm av opencv-python
2. Download the scanpathvis.py file to your computer

marc-tonsen

import time
import cv2
import numpy as np

# https://github.com/pupil-labs/pyndsi/tree/v1.0
import ndsi  # Main requirement

SENSOR_TYPES = ["video", "gaze"]
SENSORS = {}  # Will store connected sensors

marc-tonsen

import numpy as np

# Opening `*.time` files
time = np.fromfile(path_time, dtype="<u8")


# Opening `gaze ps*.raw` files
gaze = np.fromfile(path_gaze, dtype="<f4")
# Reshaping to (N, 2)
gaze.shape = (-1, 2) 

marc-tonsen