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pipeline:window:cryolo [2019/07/10 20:56]
twagner [Configuration] 		pipeline:window:cryolo [2019/07/11 09:49]
twagner [Configuration]
Line 42: Line 42:
 crYOLO will automatically check if an image in full_data is available in the ''filtered'' directory. The filtering is done in parallel. If you don't want to use crYOLO's internal filtering, just remove the line and filter them manually. If you remove the line, don't forget to remove the comma at the end of the line above.  crYOLO will automatically check if an image in full_data is available in the ''filtered'' directory. The filtering is done in parallel. If you don't want to use crYOLO's internal filtering, just remove the line and filter them manually. If you remove the line, don't forget to remove the comma at the end of the line above. 
  
-<hidden **Alternativ: Using neural-network denoising with JANNI**>+<hidden **Alternative: Using neural-network denoising with JANNI**>
 <html><br></html> <html><br></html>
-Since crYOLO 1.4 you can also use neural network denoising with [[:janni|JANNI]]. The easiest way is to use the JANNI's general model ([[:janni#janni_general_model|Download here]]) but you can also [[:janni_tutorial#training_a_model_for_your_data|train JANNI for your data]]. crYOLO directly uses an interface to JANNI to filter your data, you just have to specify the path to your JANNI model, overlap of the batches (default 24), the batch size (default 16) and a path where the denoised images should be written. +Since crYOLO 1.4 you can also use neural network denoising with [[:janni|JANNI]]. The easiest way is to use the JANNI's general model ([[:janni#janni_general_model|Download here]]) but you can also [[:janni_tutorial#training_a_model_for_your_data|train JANNI for your data]]. crYOLO directly uses an interface to JANNI to filter your data, you just have to specify the path to your JANNI model, overlap of the batches (default 24), the batch size (default 3) and a path where the denoised images should be written. 
  
 To use JANNI's denoising you have to use following entry in your config.json: To use JANNI's denoising you have to use following entry in your config.json:
  
 <code> <code>
-"filter":               ["path/to/janni_model.h5",24,16,"filtered"]+"filter":               ["path/to/janni_model.h5",24,3,"filtered"]
 </code>  </code> 
  
Line 150: Line 150:
 **Alternative: Using neural-network denoising with JANNI** **Alternative: Using neural-network denoising with JANNI**
  
-Since crYOLO 1.4 you can also use neural network denoising with [[:janni|JANNI]]. The easiest way is to use the JANNI's general model ([[:janni#janni_general_model|Download here]]) but you can also [[:janni_tutorial#training_a_model_for_your_data|train JANNI for your data]]. crYOLO directly uses an interface to JANNI to filter your data, you just have to specify the path to your JANNI model, overlap of the batches (default 24), the batch size (default 16) and a path where the denoised images should be written. +Since crYOLO 1.4 you can also use neural network denoising with [[:janni|JANNI]]. The easiest way is to use the JANNI's general model ([[:janni#janni_general_model|Download here]]) but you can also [[:janni_tutorial#training_a_model_for_your_data|train JANNI for your data]]. crYOLO directly uses an interface to JANNI to filter your data, you just have to specify the path to your JANNI model, overlap of the batches (default 24), the batch size (default 3) and a path where the denoised images should be written. 
  
 To use JANNI's denoising you have to use following entry in your config.json: To use JANNI's denoising you have to use following entry in your config.json:
  
 <code> <code>
-"filter":               ["path/to/janni_model.h5",24,16,"filtered"]+"filter":               ["path/to/janni_model.h5",24,3,"filtered"]
 </code>  </code> 
  
Line 267: Line 267:
         "max_box_per_image":    700,         "max_box_per_image":    700,
         "num_patches":          1,         "num_patches":          1,
-        "filter":               [0.1,"tmp_filtered"]+        "filter":               ["gmodel_janni_20190703.h5",24,3,"tmp_filtered_nn"]
       }       }
     }     }
 </code> </code>
 +
 +You can download the file ''gmodel_janni_20190703.h5'' [[https://github.com/MPI-Dortmund/sphire-janni/tree/master/janni_general_models|here]]
 </hidden> </hidden>
 <html><br></html> <html><br></html>
pipeline/window/cryolo.txt ยท Last modified: 2021/02/19 10:00 by twagner

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