| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: int64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': avocado |
| '1': rockmelon |
| '2': apple |
| '3': orange |
| '4': strawberry |
| '5': mango |
| '6': capsicum |
| splits: |
| - name: train |
| num_bytes: 549952890 |
| num_examples: 565 |
| download_size: 549981336 |
| dataset_size: 549952890 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # Fruit Detection Worldwide |
|
|
| A dataset for object detection of various fruits. The dataset contains 565 images with 3,132 bounding box annotations across 7 categories. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @Article{s16081222, |
| AUTHOR = {Sa, Inkyu and Ge, Zongyuan and Dayoub, Feras and Upcroft, Ben and Perez, Tristan and McCool, Chris}, |
| TITLE = {DeepFruits: A Fruit Detection System Using Deep Neural Networks}, |
| JOURNAL = {Sensors}, |
| VOLUME = {16}, |
| YEAR = {2016}, |
| NUMBER = {8}, |
| ARTICLE-NUMBER = {1222}, |
| URL = {https://www.mdpi.com/1424-8220/16/8/1222}, |
| ISSN = {1424-8220}, |
| DOI = {10.3390/s16081222} |
| } |
| ``` |
