Helper library for downloading OpenImages(https://storage.googleapis.com/openimages/web/index.html) categorically.
Open Images is the largest annotated image dataset in many regards, for use in training the latest deep convolutional neural networks for computer vision tasks. But, sometimes large capacities of 'Open Images' make it difficult to find only the data you need.
Then you can easily get data with this code including Bounding Boxes (600 classes), Object Segmentations, Visual Relationships, and Localized Narratives.
This code needs 'ratelim', 'tqdm' and 'checkpoint'. Both 'tqdm' and 'checkpoint' are included in this repository. But you need to install a 'ratelim' using the code below before running.
pip install ratelim
usage: EasyDownloader.py [-h] [--category CATEGORY] [--type TYPE] [--ndata NDATA]
[--label LABEL] [--annotation ANNOTATION] [--imageURL IMAGEURL]
[--savepath SAVEPATH]
optional arguments:
-h, --help show this help message and exit
--category CATEGORY Enter the category you want. If you want multi-
category, please tag each category.
--type TYPE Enter the type of data you want. If you want 'Union
data' enter 'sum' else if you want 'intersection data'
enter 'inter'.
--ndata NDATA Number of data you want
--label LABEL Path of class descriptions file.
--annotation ANNOTATION
Path of bbox annotation file.
--imageURL IMAGEURL Path of imageURL file.
--savepath SAVEPATH Path where downloaded data will be saved
### If you use this code at colab, add '!' at the beginning of the line.
python EasyDownloader.py --category "Football" --category "Person" --type "inter" --savepath "Football_data"
In this example, you can get images that have both 'football category' and 'personal category' in each image.
If you enter "sum" instead of "inter", you can get images that have 'Football category' or 'Person category' in each image.
Image is saved at "{--savepath}/images/[imageURL].jpg".
Information of bbox is saved at "{--savepath}/bbox/bbox_data.csv".
Information of label is saved at "{--savepath}/bbox/label_data.csv".
You can use name of imagefile and column('OriginalURL') of 'bbox.csv' to match annotation to image.
### Too many calls in a short time can lead to missing data.
@ratelim.patient(5, 5) # 5 times in 5 seconds (Gets called at most every 1. seconds)
@ratelim.patient(10, 5) # 10 times in 5 seconds (Gets called at most every 0.5 seconds)