uisikdag/weed_yolov8_imbalanced

Supported Labels

['Black-grass', 'Charlock', 'Cleavers', 'Common Chickweed', 'Common wheat', 'Fat Hen', 'Loose Silky-bent', 'Maize', 'Scentless Mayweed', 'Shepherds Purse', 'Small-flowered Cranesbill', 'Sugar beet']

How to use

• Install ultralyticsplus:

pip install ultralyticsplus==0.0.28 ultralytics==8.0.43

• Load model and perform prediction:

from ultralyticsplus import YOLO, postprocess_classify_output

# load model
model = YOLO('uisikdag/weedyolov8')

# set model parameters
model.overrides['conf'] = 0.25  # model confidence threshold

# set image
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'

# perform inference
results = model.predict(image)

# observe results
print(results[0].probs) # [0.1, 0.2, 0.3, 0.4]
processed_result = postprocess_classify_output(model, result=results[0])
print(processed_result) # {"cat": 0.4, "dog": 0.6}