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sbb_pixelwise_segmentation
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sbb_pixelwise_segmentation/config_params.json

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📝 howto: Be more verbose with the subtree pull
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{
integrating first working classification training model
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"model_name" : "resnet50_unet",
"task": "classification",
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"n_classes" : 2,
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"n_epochs" : 7,
"input_height" : 224,
"input_width" : 224,
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"weight_decay" : 1e-6,
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"n_batch" : 6,
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"learning_rate": 1e-4,
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"f1_threshold_classification": 0.8,
"patches" : false,
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"pretraining" : true,
continue training, losses and etc
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"augmentation" : false,
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"flip_aug" : false,
continue training, losses and etc
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"blur_aug" : false,
"scaling" : true,
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"binarization" : false,
"scaling_bluring" : false,
"scaling_binarization" : false,
first updates, padding, rotations
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"scaling_flip" : false,
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"rotation": false,
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"rotation_not_90": false,
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"num_patches_xy": [28, 28],
"transformer_patchsize": 1,
"blur_k" : ["blur","guass","median"],
"scales" : [0.6, 0.7, 0.8, 0.9, 1.1, 1.2, 1.4],
"brightness" : [1.3, 1.5, 1.7, 2],
"degrade_scales" : [0.2, 0.4],
"flip_index" : [0, 1, -1],
"thetha" : [10, -10],
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"continue_training": false,
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"index_start" : 0,
"dir_of_start_model" : " ",
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"weighted_loss": false,
"is_loss_soft_dice": false,
"data_is_provided": false,
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"dir_train": "/home/vahid/Downloads/image_classification_data/train",
"dir_eval": "/home/vahid/Downloads/image_classification_data/eval",
"dir_output": "/home/vahid/Downloads/image_classification_data/output"
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}