Object Detection
ultralytics
English
biology
CV
images
animals
YOLO
fine-tuned
zebra
giraffe
onager
dog
Instructions to use imageomics/mmla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use imageomics/mmla with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("imageomics/mmla") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
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- mAP50-95
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base_model:
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- Ultralytics/YOLO11
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---
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# Model Card for Fine-Tuned YOLOv11m Animal Detection Model
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- mAP50-95
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base_model:
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- Ultralytics/YOLO11
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model_description: >-
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This model is a fine-tuned version of YOLOv11m optimized for detection
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and classification of wildlife from low-altitude drone imagery.
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It has been trained to identify zebras (Plains and Grevy's),
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giraffes (reticulated and Masai), Persian onagers, and African Painted
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dogs with high accuracy across diverse environmental conditions.
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# Model Card for Fine-Tuned YOLOv11m Animal Detection Model
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