Instructions to use FriedParrot/fish-segmentation-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FriedParrot/fish-segmentation-simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="FriedParrot/fish-segmentation-simple")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageSegmentation processor = AutoImageProcessor.from_pretrained("FriedParrot/fish-segmentation-simple") model = AutoModelForImageSegmentation.from_pretrained("FriedParrot/fish-segmentation-simple") - Notebooks
- Google Colab
- Kaggle
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README.md
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* **Batch size**: use 8 as train batch sizes
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* **Training strategy**: Direct fine-tuning of DETR with minimal modifications
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## Results & Example Predictions
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* **Batch size**: use 8 as train batch sizes
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* **Training strategy**: Direct fine-tuning of DETR with minimal modifications
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## Results & Example Predictions
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Since its a fine-tuned model, the accuracy is really high, and also classification accuracy can reach about 100%.
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The predicted bounding box and masks are also very accurate :
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