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apache-2.0 |
Basic Shapes Object Detection |
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This Basic Shapes Object Detection dataset has been created to test fine-tuning of object detection models. Fine-tuning some model to detect the basic shapes should be rather easy: just a bit of training should be enough to get the model to do correct object detection quite fast.
Each entry in the dataset has a RGB PNG image with a white background and 3 basic geometric shapes:
- A blue square
- A red circle
- A green triangle
All images have the same size. Each image has exactly 1 square, 1 circle and 1 triangle, with their fixed colors. Each entry in the dataset has consequently 3 bounding boxes. The shapes do not overlap.The category IDs are 0, 1 and 2, corresponding to the labels Square, Circle and Triangle.
The dataset has exactly the same structure as the https://huggingface.co/datasets/cppe-5 dataset, but fine-tuning some model to this dataset with basic geometric shapes should require considerable less training compared to the cppe-5 dataset. Once you have tested your fine-tuning code on this dataset, it should also work on more complicated datasets such as the cppe-5 dataset.
The Python code to generate the images can be found at https://github.com/DriesVerachtert/basic_shapes_object_detection_dataset The dataset can be downloaded from https://huggingface.co/datasets/driesverachtert/basic_shapes_object_detection
The bounding boxes are in COCO format (x_min, y_min, width, height).
This dataset is released under Apache 2.0.
from datasets import load_dataset
dataset = load_dataset("driesverachtert/basic_shapes_object_detection")