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Modify parameters
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@Mmasoud1
Mmasoud1 committed Mar 30, 2024
1 parent 12f6b33 commit 2f8db70
Showing 1 changed file with 16 additions and 16 deletions.
32 changes: 16 additions & 16 deletions js/brainchop/mainParameters.js
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Original file line number Diff line number Diff line change
Expand Up @@ -113,8 +113,8 @@
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 0, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: false, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 2, // Padding size add to cropped brain
autoThreshold: 0.1, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
Expand Down Expand Up @@ -182,14 +182,14 @@
modelName:"\u{1FA93} Subcortical + GWM (High Mem, Fast)",
labelsPath: "./models/model18cls/labels.json",
colorsPath: "./models/model18cls/colorLUT.json",
preModelId: null,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelId: 1,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: false, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand All @@ -206,14 +206,14 @@
modelName:"\u{1FA93} Subcortical + GWM (Low Mem, Slow)",
labelsPath: "./models/model18cls/labels.json",
colorsPath: "./models/model18cls/colorLUT.json",
preModelId: null,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelId: 1,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: true, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand All @@ -230,14 +230,14 @@
modelName:"\u{1FA93} Subcortical + GWM (Low Mem, Faster)",
labelsPath: "./models/model30chan18cls/labels.json",
colorsPath: "./models/model30chan18cls/colorLUT.json",
preModelId: null, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelId: 1, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: true, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand All @@ -254,14 +254,14 @@
modelName:"\u{1F52A} Aparc+Aseg 50 (High Mem, Fast)",
labelsPath: "./models/model30chan50cls/labels.json",
colorsPath: "./models/model30chan50cls/colorLUT.json",
preModelId: null,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelId: 1,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: true, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: false, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand All @@ -278,14 +278,14 @@
modelName:"\u{1F52A} Aparc+Aseg 50 (Low Mem, Slow)",
labelsPath: "./models/model30chan50cls/labels.json",
colorsPath: "./models/model30chan50cls/colorLUT.json",
preModelId: null,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelId: 1,// Model run first e.g. crop the brain { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: true, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: true, // For low memory system and low configuration, enable sequential convolution instead of last laye
Expand Down Expand Up @@ -399,14 +399,14 @@
modelName:"\u{1F52A} Aparc+Aseg 104 (High Mem, Fast)",
labelsPath: "./models/model21_104class/labels.json",
colorsPath: "./models/model21_104class/colorLUT.json",
preModelId: null, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelId: 1, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: false, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand All @@ -423,14 +423,14 @@
modelName:"\u{1F52A} Aparc+Aseg 104 (Low Mem, Slow)",
labelsPath: "./models/model21_104class/labels.json",
colorsPath: "./models/model21_104class/colorLUT.json",
preModelId: null, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelId: 1, // model run first e.g. Brain_Extraction { null, 1, 2, .. }
preModelPostProcess: false, // If true, perform postprocessing to remove noisy regions after preModel inference generate output.
isBatchOverlapEnable: false, //create extra overlap batches for inference
numOverlapBatches: 200, //Number of extra overlap batches for inference
enableTranspose : true, // Keras and tfjs input orientation may need a tranposing step to be matched
enableCrop: true, // For speed-up inference, crop brain from background before feeding to inference model to lower memory use.
cropPadding: 0, // Padding size add to cropped brain
autoThreshold: 0.2, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
autoThreshold: 0, // Threshold between 0 and 1, given no preModel and tensor is normalized either min-max or by quantiles. Will remove noisy voxels around brain
enableQuantileNorm: false, // Some models needs Quantile Normaliztion.
filterOutWithPreMask: false, // Can be used to multiply final output with premodel output mask to crean noisy areas
enableSeqConv: true, // For low memory system and low configuration, enable sequential convolution instead of last layer
Expand Down

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