GrapesNet: Indian RGB & RGB-D Vineyard Image Datasets

Tracking #: 744-1724


Responsible editor: 

Tobias Kuhn

Submission Type: 

Resource Paper


In most of the countries, grapes are considered as a cash crop. Currently huge research is going on in development of automated grape harvesting systems. Speedy and reliable grape bunch detection is prime need for various deep learning based automated systems which deals with object detection and object segmentation tasks. But currently very few datasets are available on grape bunches in vineyard, because of which there is restriction to the research in this area. In comparison to the vineyard in outside countries, Indian vineyard structure is more complex, so it becomes hard to work in real-time. To overcome these problems and to make vineyard dataset for suitable for Indian vineyard scenarios, this paper proposed four different datasets on grape bunches in vineyard. For creating all datasets in GrapesNet, natural environmental conditions have been considered. GrapesNet includes total 11000+ images of grape bunches. Proposed datasets can be used for prime tasks like grape bunch detection, grape bunch segmentation, and grape bunch weight estimation etc. of future generation automated vineyard harvesting technologies.



  • Under Review

Data repository URLs: 

Date of Submission: 

Monday, January 23, 2023

1 Comment

Review the paper and comment.


-Provides a comprehensive overview of the current research and challenges in developing automated grape harvesting systems.

-Discusses the need for datasets that can accommodate the complexities of Indian vineyard structures. -Proposes four different datasets of grape bunches in vineyard and provides details on the number of images and tasks that can be used.

Negative: -Does not provide any details on the collection process of the datasets. -

Does not include any experiments or results to demonstrate the effectiveness of the proposed datasets.


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  3. Introduction should be of 5-7 solid paragraphs and provide structure of work at the end of the Introduction section.
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  8. Please avoid to write definitions of terms like Artificial intelligence, grape bunch segmentation, vineyard dataset etc., which are already available over web, try to cite work for such information.
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