Yolov8x Visdrone

🚀 mshamrai/yolov8x-visdrone

該模型基於ultralytics庫，屬於目標檢測模型，可對多種常見目標進行檢測，適用於相關的視覺應用場景。

🚀 快速開始

支持的標籤

['pedestrian', 'people', 'bicycle', 'car', 'van', 'truck', 'tricycle', 'awning-tricycle', 'bus', 'motor']

使用步驟

1. 安裝 ultralyticsplus：

pip install ultralyticsplus==0.0.28 ultralytics==8.0.43

2. 加載模型並進行預測：

from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('mshamrai/yolov8x-visdrone')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # maximum number of detections per image

# 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].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()

📦 模型信息