| license: mit | |
| base_model: ultralytics/yolov8n-cls | |
| tags: | |
| - ultralytics | |
| - yolo | |
| - vision | |
| - image-classification | |
| - pytorch | |
| - insects | |
| - pollinators | |
| - biodiversity | |
| - ecology | |
| - conservation | |
| datasets: | |
| - custom | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: pollinator-classifier | |
| results: | |
| - task: | |
| type: image-classification | |
| name: Image Classification | |
| dataset: | |
| name: Custom Pollinator Insects Dataset | |
| type: custom | |
| metrics: | |
| - type: accuracy | |
| value: 0.9207 | |
| name: Top-1 Accuracy | |
| - type: accuracy | |
| value: 0.9912 | |
| name: Top-5 Accuracy | |
| pipeline_tag: image-classification | |
| # Pollinator Insect Classifier 🔬 | |
| High-precision classifier for 10 pollinator insect species using YOLOv8 Nano with **92.07% accuracy**. | |
| ## Quick Start | |
| ```python | |
| from ultralytics import YOLO | |
| from huggingface_hub import hf_hub_download | |
| # Download model | |
| model_path = hf_hub_download("leonelgv/pollinator-classifier", "yolo8n.pt") | |
| # Load and predict | |
| model = YOLO(model_path) | |
| results = model("insect_image.jpg") | |
| ``` | |
| See files in this repository for complete usage examples and training details. | |