dataset_info:
features:
- name: image
dtype: image
- name: split
dtype: string
- name: width
dtype: int64
- name: height
dtype: int64
- name: bboxes
dtype: string
- name: labels
dtype: string
- name: gaze_item
dtype: int64
- name: gazeIdx
dtype: int64
- name: gaze_cx
dtype: int64
- name: gaze_cy
dtype: int64
- name: hx
dtype: int64
- name: hy
dtype: int64
- name: seg
dtype: string
- name: occluded
dtype: bool
- name: person_num
dtype: int64
- name: cam_num
dtype: int64
splits:
- name: test
num_bytes: 6289998121.391
num_examples: 7391
download_size: 6286282416
dataset_size: 6289998121.391
The dataset features/columns here are almost similar to the original github instruction (please read the github documentation first to understand the dataset): https://github.com/upeee/GOO-GAZE2021/blob/main/dataset/gooreal-download.txt
To download gooreal in huggingface, run the code below (https://huggingface.co/docs/datasets/v1.10.0/loading_datasets.html#from-the-huggingface-hub):
from datasets import load_dataset
dataset = load_dataset("markytools/goorealv3")
The image datasets will be stored in ""~/.cache/huggingface", so you need to delete the files here if you want to free up space.
The "bboxes" and "labels" features are in string format, so you can use the code below to convert the string into list:
import ast
listOfBboxes = ast.literal_eval(dataset["test"]["bboxes"][0])
The feature "seg" is now in string format instead of numpy ndarray. This is an optional feature, and you can manually download the files here (https://huggingface.co/datasets/markytools/goosegmv3) using wget commandline. The files are in .npy so load it using np.load (https://numpy.org/doc/stable/reference/generated/numpy.load.html).