Object Detection
ultralytics
ONNX
yolov11
efficientnet
electroluminescence
photovoltaic
solar-energy
Instructions to use azizasyd/yolov11-el-fault-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use azizasyd/yolov11-el-fault-detector with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("azizasyd/yolov11-el-fault-detector") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
YOLOv11‑EfficientNet EL Fault Detector
This model detects micro‑cracks, finger interruptions, short circuits, and dislocations in electroluminescence (EL) images of photovoltaic cells.
- Backbone: EfficientNet‑B0
- Detector: YOLOv11 (Ultralytics)
- Classes: 8 PV‑fault categories
- Weights:
best_quant.onnx(INT8) · 84 MB
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