Instructions to use driesverachtert/basic_shapes_object_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use driesverachtert/basic_shapes_object_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="driesverachtert/basic_shapes_object_detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("driesverachtert/basic_shapes_object_detection") model = AutoModelForObjectDetection.from_pretrained("driesverachtert/basic_shapes_object_detection") - Notebooks
- Google Colab
- Kaggle
Basic Shapes Object Detection Model
Description
This is a model based on facebook/detr-resnet-50 which is fine-tuned to detect very basic shapes like circles, squares and triangles.
It's trained on the dataset at https://huggingface.co/datasets/driesverachtert/basic_shapes_object_detection . The code which was used to create that dataset can be found at https://github.com/DriesVerachtert/basic_shapes_object_detection_dataset
This model itself can be downloaded from the HuggingFace Hub at https://huggingface.co/driesverachtert/basic_shapes_object_detection . The code which was used to train the model can be found at https://github.com/DriesVerachtert/basic_shapes_object_detection_model
License
This model is released under Apache 2.0.
Useful links
- https://github.com/facebookresearch/detr
- https://huggingface.co/facebook/detr-resnet-50
- https://huggingface.co/docs/transformers/main/en/tasks/object_detection
- https://huggingface.co/docs/transformers/main/en/model_doc/detr
- https://github.com/Rishit-dagli/CPPE-Dataset
Contact
Dries Verachtert - dries.verachtert@dries.eu https://www.linkedin.com/in/dries/
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