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---
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</br>
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.
</br>
The "bboxes" and "labels" features are in string format, so you can use the code below to convert the string into list:</br>
import ast</br>
listOfBboxes = ast.literal_eval(dataset["test"]["bboxes"][0])</br>
</br>
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). |