Datasets:
Size:
10K<n<100K
License:
| license: cc-by-nc-sa-4.0 | |
| task_categories: | |
| - image-segmentation | |
| - depth-estimation | |
| tags: | |
| - agriculture | |
| - synthetic-data | |
| - tomato | |
| - plant-disease | |
| size_categories: | |
| - 10K<n<100K | |
| # Dataset Summary | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** | |
| - **Repository:** | |
| - **Paper:** | |
| - **Leaderboard:** | |
| - **Point of Contact:** | |
| ### Dataset Summary | |
| This dataset consist of 21,384 2448x2048 pairs of synthetic images for tomato plants. Each pair consist of left/right RGBD, and panoptic segmentation labels for the left image. See `example_load.py` for usage. | |
| ### Supported Tasks and Leaderboards | |
| - `image-segmentation`: Both panoptic and semantic labels for separating tomato plants and identifying features and disease types in the dataset. | |
| - `depth-estimation`: ground truth depth values for stereo and monocular applications. | |
| ### Languages | |
| English | |
| ## Dataset Structure | |
| ### Data Instances | |
| Each datapoint consist of 6 images: | |
| ``` | |
| { | |
| 'left_rgb': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2448x2048 at 0x7F63FB5F4350>, | |
| 'right_rgb': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2448x2048 at 0x7F63FF2B3950>, | |
| 'left_semantic': <PIL.PngImagePlugin.PngImageFile image mode=L size=2448x2048 at 0x7F63FC4488C0>, | |
| 'left_instance': <PIL.TiffImagePlugin.TiffImageFile image mode=I;16 size=2448x2048 at 0x7F63FC497EF0>, | |
| 'left_depth': <PIL.TiffImagePlugin.TiffImageFile image mode=F size=2448x2048 at 0x7F63FACF6E70>, | |
| 'right_depth': <PIL.TiffImagePlugin.TiffImageFile image mode=F size=2448x2048 at 0x7F63FACF7560> | |
| } | |
| ``` | |
| ### Data Fields | |
| - 'left_rgb': Left RGB image, was compressed to 95\% quality. | |
| - 'right_rgb': Right RGB image, was compressed to 95\% quality. Note the baseline is 3.88112 cm and HFOV is 95.452621 degrees. | |
| - 'left_semantic': Rendered colors that denotes the RGB label for individual pixels. See `example_load.py` for classes and sample scripts. | |
| - 'left_instance': Rendered colors that denotes the tomato plant instances for individual pixels. | |
| - 'left_depth': Rendered left depth compressed to 16-bit floats (in centimeters). | |
| - 'right_depth': Rendered right depth compressed to 16-bit floats (in centimeters). | |
| ### Data Splits | |
| 80/20 as shown in the train.txt and val.txt. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| Created to provide dataset for dense plant disease detection for an agricultural research robotics platform with corresponding camera sensors and strobe lighting. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| We used PlantVillage Dataset with further processing to align the healthy leaf colors with the purchased assets. We collected 750GB of original data where we compressed the depth images from 32-bit to 16-bit and RGB to 95\% quality for ~160GB. | |
| #### Who are the source language producers? | |
| See PlantVillage Datasets for tomato diseases. The tomato plants were purchased through SketchFab with modifications for extra green tomatoes and denser leaves. | |
| ### Annotations | |
| #### Annotation process | |
| Annotations automatically generated through the simulation. | |
| #### Who are the annotators? | |
| Same as data creators. Tomato leaf diseases the same as PlantVillage creators. | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [More Information Needed] | |
| ### Licensing Information | |
| CC BY-NC-SA-4.0 | |
| ### Citation Information | |
| [More Information Needed] | |
| ### Contributions | |
| [More Information Needed] | |