Datasets:
rgautroncgiar
commited on
Commit
•
cd20a3b
1
Parent(s):
96c6b35
minor changes README
Browse files
README.md
CHANGED
@@ -29,9 +29,11 @@ license_link: https://www.gnu.org/licenses/quick-guide-gplv3.html
|
|
29 |
---
|
30 |
[Croppie](https://croppie.org/) © 2024 by [Producers Direct](https://producersdirect.org/) and [Alliance Bioversity & CIAT](https://alliancebioversityciat.org/) is licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
|
31 |
|
|
|
|
|
32 |
# Croppie training datasets
|
33 |
## General information
|
34 |
-
Croppie dataset for machine-vision assisted coffee cherry detection. The dataset is made of a mix of Arabica and Robusta coffee tree parts (with and without a background isolation element) with individual bounding boxes around all coffee cherries.
|
35 |
|
36 |
The original dataset is composed of 633 images with about 61 050 unique bounding boxes over coffee cherries in YOLO format. This original dataset has been processed to cut-down all images into 480 x 640 size pieces and the full original image downscaled to 480 x 640. We provide the processed dataset with Python scripts that allow easy visualization of the annotated dataset.
|
37 |
|
@@ -92,4 +94,8 @@ Assuming you are in the ```scripts``` folder, first
|
|
92 |
```python3 label_training_images.py```
|
93 |
|
94 |
## License
|
95 |
-
[Croppie](https://croppie.org/) © 2024 by [Producers Direct](https://producersdirect.org/) and [Alliance Bioversity & CIAT](https://alliancebioversityciat.org/) is licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
|
|
|
|
|
|
|
|
|
|
29 |
---
|
30 |
[Croppie](https://croppie.org/) © 2024 by [Producers Direct](https://producersdirect.org/) and [Alliance Bioversity & CIAT](https://alliancebioversityciat.org/) is licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
|
31 |
|
32 |
+
**Funded by**: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) [Fair Forward Initiative - AI for All](https://huggingface.co/fair-forward)
|
33 |
+
|
34 |
# Croppie training datasets
|
35 |
## General information
|
36 |
+
Croppie dataset for machine-vision assisted coffee cherry detection. The dataset is made of a mix of Arabica and Robusta coffee tree parts (with and without a background isolation element) with individual bounding boxes around all coffee cherries. These RGB pictures were on-farm collected with smartphones with the collaboration of smallholder farmers. For instance, this dataset can be used for automated cherry count or coffee ripeness assessment.
|
37 |
|
38 |
The original dataset is composed of 633 images with about 61 050 unique bounding boxes over coffee cherries in YOLO format. This original dataset has been processed to cut-down all images into 480 x 640 size pieces and the full original image downscaled to 480 x 640. We provide the processed dataset with Python scripts that allow easy visualization of the annotated dataset.
|
39 |
|
|
|
94 |
```python3 label_training_images.py```
|
95 |
|
96 |
## License
|
97 |
+
[Croppie](https://croppie.org/) © 2024 by [Producers Direct](https://producersdirect.org/) and [Alliance Bioversity & CIAT](https://alliancebioversityciat.org/) is licensed under [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
|
98 |
+
|
99 |
+
## Funding
|
100 |
+
|
101 |
+
**Funded by**: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) [Fair Forward Initiative - AI for All](https://huggingface.co/fair-forward)
|