import gradio as gr from ultralyticsplus import YOLO, render_result # load model model = YOLO("keremberke/yolov8m-hard-hat-detection") # 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 def get_result(img): results = model.predict(img) return render_result(model=model, image=img, result=results[0]) title = "Hard Hat Detector" description = "Upload an image to identify who is wearing a hard hat and who is not." examples = ["https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg"] iface = gr.Interface( title=title, description=description, examples=examples, fn=get_result, inputs=gr.components.Image(shape=(512, 512)), outputs=gr.components.Image(shape=(512, 512)), ) iface.launch()