Create App2.py

App2.py

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+from ultralyticsplus import YOLO, render_result
+
+# load model
+model = YOLO('keremberke/yolov8n-pcb-defect-segmentation')
+
+# 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)
+print(results[0].masks)
+render = render_result(model=model, image=image, result=results[0])
+render.show()