import glob import gradio as gr from ultralytics import YOLO model_path = "best.pt" model = YOLO(model_path) PREDICT_KWARGS = { "classes": 0, "conf": 0.25, } def run(image_path): results = model.predict(image_path, **PREDICT_KWARGS) return results[0].plot()[:, :, ::-1] # reverse channels for gradio title = "Megalodon Detector" description = ( "" ) examples = glob.glob("images/*.png") interface = gr.Interface( run, inputs=[gr.components.Image(type="filepath")], outputs=gr.components.Image(type="numpy"), title=title, description=description, examples=examples, ) interface.queue().launch()