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/goosynth-download.txt

To download goosynthtrain 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/goosyntheticv3")

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 only difference here is that there is a new feature name called "splits", ["train", "test"] </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).
region:us
{"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": "cab", "dtype": "int64"}, {"name": "hum", "dtype": "int64"}, {"name": "light", "dtype": "float64"}, {"name": "cam", "dtype": "int64"}, {"name": "env", "dtype": "int64"}, {"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": "pitch", "dtype": "float64"}, {"name": "yaw", "dtype": "float64"}, {"name": "roll", "dtype": "float64"}, {"name": "seg", "dtype": "string"}, {"name": "segm_gazeIdx", "dtype": "int64"}, {"name": "occluded", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 99500978350.0, "num_examples": 172800}, {"name": "test", "num_bytes": 11081866319.6, "num_examples": 19200}], "download_size": 110113558133, "dataset_size": 110582844669.6}}
TAGS
#region-us 

The dataset features/columns here are almost similar to the original github instruction (please read the github documentation first to understand the dataset): URL

To download goosynthtrain in huggingface, run the code below (URL

from datasets import load_dataset</br>
dataset = load_dataset("markytools/goosyntheticv3")

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 only difference here is that there is a new feature name called "splits", ["train", "test"] </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 (URL using wget commandline. The files are in .npy so load it using URL (URL
TAGS
#region-us 

passage: TAGS
#region-us 
