Answers.Body: <p>It is much better to know basic mechanics of convnets first ,rather than diving straight into complicated models .</p>
  
  <p><em>For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise. Can I use these images for training? Also, which yolo version should I use? What are the important points that I should consider for training datasets?</em> </p>
  
  <p>After you are good with the theory part most of your questions will be answered , otherwise you would endup with nothing but buzzwords.</p>
  
  <p><em>I want to use any version of yolo compatible with tensorflow.</em></p>
  
  <p>Tensorflow is a framework for building neural networks , so in theory you can build any network with it so compatibility is not at all a problem.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-07-02T12:46:06.317Z
Answers.LastActivityDate: 2018-07-03T04:26:43.007Z
Answers.LastEditDate: 2018-07-03T04:26:43.007Z
Answers.UserDisplayName: thecomplexitytheorist
Answers.Body: <p>As long as all training samples have same type and level of noise, it shouldn't affect the outcome/accuracy.</p>
  <p>As far as real time performance is concerned, you should compare the &quot;Params, FLops and Inference time @ B1 (Batch size 1)&quot; numbers of different yolo versions.
  Lower the number, faster the inference.</p>
  <p>You can start by exploring yolov5 and Yolo-Fastestv2 at the links below:</p>
  <p><a href="https://github.com/ultralytics/yolov5" rel="nofollow noreferrer">https://github.com/ultralytics/yolov5</a></p>
  <p><a href="https://github.com/dog-qiuqiu/Yolo-FastestV2" rel="nofollow noreferrer">https://github.com/dog-qiuqiu/Yolo-FastestV2</a></p>
  <p>Unfortunately most of the implementations are in PyTorch, but you can easily convert a PyTorch model to a Tensorflow one by first converting it to an ONNX format.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-08-09T15:58:58.143Z
Answers.LastActivityDate: 2022-08-09T15:58:58.143Z
Answers.UserDisplayName: Marib Sultan
Body: <p>I want to detect drivers with or without seatbelts at crossroads. For that, as it is real-time, I am going to use the YOLO algorithm/model. For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise. </p>
  
  <p>Can I use these images for training? Also, which YOLO version should I use? What are the important points that I should consider for training datasets?</p>
  
  <p>I want to use any version of YOLO compatible with TensorFlow.</p>
  
Tags: <machine-learning><deep-learning><tensorflow><yolo>
Title: What YOLO algorithm can I use for images with noise as I will implement it in real time?
UserDisplayName: ťęjă RAVURI
ThreadText: # What YOLO algorithm can I use for images with noise as I will implement it in real time?
  
  (Asked by: username_0 on 2018-07-01)
  
  I want to detect drivers with or without seatbelts at crossroads. For that, as it is real-time, I am going to use the YOLO algorithm/model. For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise.
  
  Can I use these images for training? Also, which YOLO version should I use? What are the important points that I should consider for training datasets?
  
  I want to use any version of YOLO compatible with TensorFlow.
  
  **Tags:** machine-learning, deep-learning, tensorflow, yolo
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2018-07-02. Score: 1
  
  It is much better to know basic mechanics of convnets first ,rather than diving straight into complicated models .
  
  *For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting images from there, I am getting images with more noise. Can I use these images for training? Also, which yolo version should I use? What are the important points that I should consider for training datasets?*
  
  After you are good with the theory part most of your questions will be answered , otherwise you would endup with nothing but buzzwords.
  
  *I want to use any version of yolo compatible with tensorflow.*
  
  Tensorflow is a framework for building neural networks , so in theory you can build any network with it so compatibility is not at all a problem.
  
  
  ---
  
  ### Answer by username_2 on 2022-08-09. Score: 0
  
  As long as all training samples have same type and level of noise, it shouldn't affect the outcome/accuracy.
  
  As far as real time performance is concerned, you should compare the "Params, FLops and Inference time @ B1 (Batch size 1)" numbers of different yolo versions.
  Lower the number, faster the inference.
  
  You can start by exploring yolov5 and Yolo-Fastestv2 at the links below:
  
  <https://github.com/ultralytics/yolov5>
  
  <https://github.com/dog-qiuqiu/Yolo-FastestV2>
  
  Unfortunately most of the implementations are in PyTorch, but you can easily convert a PyTorch model to a Tensorflow one by first converting it to an ONNX format.
  
  
  ---
  
  