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NMS confidence threshold\nmodel.overrides['iou'] = 0.45  # NMS IoU threshold\nmodel.overrides['agnostic_nms'] = False  # NMS class-agnostic\nmodel.overrides['max_det'] = 1000  # maximum number of detections per image\n\n# set image\nimage = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'\n\n# perform inference\nresults = model.predict(image, imgsz=640)\n\n# parse results\nresult = results[0]\nboxes = result.boxes.xyxy # x1, y1, x2, y2\nscores = result.boxes.conf\ncategories = result.boxes.cls\nscores = result.probs # for classification models\nmasks = result.masks # for segmentation models\n\n# show results on image\nrender = render_result(model=model, image=image, result=result)\nrender.show()\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffcakyon%2Fultralyticsplus","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffcakyon%2Fultralyticsplus","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffcakyon%2Fultralyticsplus/lists"}