How to use
- Install yolov5:
pip install -U yolov5
- Load model and perform prediction:
import yolov5
model = yolov5.load('MBARI-org/megamidwater')
# Run the yolo
# set model parameters
model.conf = 0.25 # NMS confidence threshold
model.iou = 0.1 # NMS IoU threshold
model.agnostic = False # NMS class-agnostic
model.multi_label = False # NMS multiple labels per box
model.max_det = 1000 # maximum number of detections per image
# set image
img = 'http://dsg.mbari.org/images/dsg/external/Ctenophora/Deiopea_01.png'
# perform inference
results = model(img, size=1280)
# print results
print(results.pandas().xyxy[0])
- Finetune the model on your custom dataset:
yolov5 train --data data.yaml --img 1280 --batch 16 --weights mbari-org/megamidwater --epochs 10
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Inference Providers
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Evaluation results
-
self-reported
0.736