Answers.Body: <p>It is better to crop the image, rather than scaling it to 53% width and 95% height. Otherwise your objects would have skewed aspect ratio, for example balls would seem elliptical.</p>
  <p>Since your camera's resolution is larger than the network's input, in theory there is no loss of image quality there. But the camera might have a very poor image quality to begin with, having only about two megapixels. Several things affect this, such as optics, the image sensor and the amount of ambient light.</p>
  <p>And 1024 x 1024 is still a fairly high resolution for most image tasks, including object detection. It may require unexpectedly high computational resources to train and apply.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-18T11:16:57.377Z
Answers.LastActivityDate: 2022-10-18T11:16:57.377Z
Answers.UserDisplayName: NikoNyrh
Body: <p>I am going to use this model for my school project. Just wondering if I bought a 1920x1080 camera, will resizing it to 1024x1024 will cause the drop of image quality(make model harder to detect object as in this case width need to resize a lot more as compare to height of the image)?</p>
  
Tags: <tensorflow>
Title: What camera resolution is good for Resnet101 SSD FPN 1024x1024
UserDisplayName: chuackt
ThreadText: # What camera resolution is good for Resnet101 SSD FPN 1024x1024
  
  (Asked by: username_0 on 2022-10-17)
  
  I am going to use this model for my school project. Just wondering if I bought a 1920x1080 camera, will resizing it to 1024x1024 will cause the drop of image quality(make model harder to detect object as in this case width need to resize a lot more as compare to height of the image)?
  
  **Tags:** tensorflow
  
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  ## 1 answers
  
  ### Answer by username_1 on 2022-10-18. Score: 0 | Accepted answer
  
  It is better to crop the image, rather than scaling it to 53% width and 95% height. Otherwise your objects would have skewed aspect ratio, for example balls would seem elliptical.
  
  Since your camera's resolution is larger than the network's input, in theory there is no loss of image quality there. But the camera might have a very poor image quality to begin with, having only about two megapixels. Several things affect this, such as optics, the image sensor and the amount of ambient light.
  
  And 1024 x 1024 is still a fairly high resolution for most image tasks, including object detection. It may require unexpectedly high computational resources to train and apply.
  
  
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