| from ultralytics import YOLO |
| import gradio as gr |
|
|
| |
| model = YOLO("yolo26n.pt") |
|
|
| def detect_objects(image, confidence: float = 0.25): |
| results = model(image, conf=confidence, verbose = False) |
| annotated_image = results[0].plot() |
| return annotated_image |
|
|
| |
| demo = gr.Interface( |
| fn=detect_objects, |
| inputs=[ |
| gr.Image(type="pil", label="Upload Image"), |
| gr.Slider(minimum=0.1, maximum=1.0, value=0.25, label="Confidence Threshold") |
| ], |
| outputs=gr.Image(label="YOLO26 Detections"), |
| title="YOLO26 Object Detection", |
| description="Upload any image to detect objects", |
| article="Random object detection thing" |
| ) |
|
|
| if __name__ == "__main__": |
| demo.launch() |