Create README.md

README.md

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