text: Title: How can improve my YOLOv5x-Seg model's precision?
  Body: ![confusion_matrix - Kopya](https://github.com/ultralytics/yolov5/assets/32833796/1b14cdcb-af36-4fcc-ad2f-3c2b4f6ef547)
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  ### Question
  
  Hi, im working on a YOLOv5 model for months. I started with YOLOv4 but then i thought should use segmentation so i used YOLOv8 and YOLOv5 for my segmentation project. After tests i took best result from YOLOv5x-Seg, so currently working with it. My project about a thing that exist in sea surface and i have to detect from satellite images. So I made a dataset that include 1000 photos (taken from satellite hub by myself and manuel segment labeled and have only one class). Because of satellite images my objects little and scattered this is the problem i guess, maybe hard to detect? Then trained a YOLOv5 model it was really bad in the beginning but i change some settings and hypermeters now not bad. After that i tried many things but cant improved more. Besides this im getting weird confusion matrix that shows FP is one and TN is zero. Can you give me any advice how to improve like over %90's. Thanks.
  ![confusion_matrix - Kopya](https://github.com/ultralytics/yolov5/assets/32833796/d4857008-a072-4286-b522-da7601e56309)
  ![results (2)zz](https://github.com/ultralytics/yolov5/assets/32833796/a2b87dde-bd05-4dea-9498-b17bd36c0b16)
  
  
  
  
  ### Additional
  
  _No response_