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Create README.md
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README.md
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---
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license:
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- unknown
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task_categories:
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- object-detection
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language:
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- en
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pretty_name: FriutDetection
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size_categories:
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- n<1K
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dataset_info:
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features:
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- name: image_id
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dtype: int64
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- name: image
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dtype: image
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- name: width
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dtype: int32
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- name: height
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dtype: int32
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- name: objects
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sequence:
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- name: bbox
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sequence: float32
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length: 4
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- name: category
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dtype:
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class_label:
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names:
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'0': Apple
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'1': Banana
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'2': Orange
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splits:
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- name: train
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num_examples: 240
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- name: test
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num_examples: 60
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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---
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# [Fruit Images for Object Detection](https://www.kaggle.com/datasets/mbkinaci/fruit-images-for-object-detection)
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Download from Kaggle datasets.
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## About Dataset
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### Project
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This dataset is the data used in this project.
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### Context
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A different dataset for object detection. 240 images in train folder. 60 images in test folder.
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### Content
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3 different fruits:
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- Apple
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- Banana
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- Orange
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### Acknowledgements
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`.xml` files were created with LabelImg. It is super easy to label objects in images.
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