Added content taken from https://osf.io/hfeu2/

model_seg_pns_bf/README.txt

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+Steps to train this model
+=========================
+
+1. Get ADS version: [5af8cbb] https://github.com/neuropoly/axondeepseg/commit/5af8cbb1e782092ac46e0586eca0f827c0eff938
+2. Get the data: Available at NeuroPoly lab in duke/projects/axondeepseg/20201016_model_seg_pns_bf/10_model_selected/dataset_training/dataset_patches/20210121_training_gps_01_filtered
+3. Run the "02-training_guideline-pns.ipynb" notebook available at NeuroPoly lab in duke/projects/axondeepseg/20201016_model_seg_pns_bf/10_model_selected/notebooks
+4. After successfully running all the cells, the trained model file will be saved under the directory: AxonDeepSeg/axondeepseg/models/
+
+Upload on OSF
+=============
+Add this README.txt file along with the model and zip the folder. 
+Model is saved in OSF under the models/ directory. Example:
+AxonDeepSeg/models/model_seg_pns_bf.zip

model_seg_pns_bf/checkpoint

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+model_checkpoint_path: "/home/GRAMES.POLYMTL.CA/maboudb/axondeepseg/notebooks/../models/Simeon_20210121_training_gps_01_filtered_2021-01-24_20-56-24/model.ckpt"
+all_model_checkpoint_paths: "/home/GRAMES.POLYMTL.CA/maboudb/axondeepseg/notebooks/../models/Simeon_20210121_training_gps_01_filtered_2021-01-24_20-56-24/model.ckpt"

model_seg_pns_bf/config_network.json

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+{
+  "n_classes": 3,
+  "thresholds": [
+    0,
+    0.2,
+    0.8
+  ],
+  "trainingset_patchsize": 512,
+  "trainingset": "20210121_training_gps_01_filtered",
+  "batch_size": 7,
+  "epochs": 400,
+  "checkpoint_period": 5,
+  "checkpoint": null,
+  "depth": 4,
+  "convolution_per_layer": [
+    3,
+    3,
+    3,
+    3
+  ],
+  "size_of_convolutions_per_layer": [
+    [
+      5,
+      5,
+      5
+    ],
+    [
+      3,
+      3,
+      3
+    ],
+    [
+      3,
+      3,
+      3
+    ],
+    [
+      3,
+      3,
+      3
+    ]
+  ],
+  "features_per_convolution": [
+    [
+      [
+        1,
+        16
+      ],
+      [
+        16,
+        16
+      ],
+      [
+        16,
+        16
+      ]
+    ],
+    [
+      [
+        16,
+        32
+      ],
+      [
+        32,
+        32
+      ],
+      [
+        32,
+        32
+      ]
+    ],
+    [
+      [
+        32,
+        64
+      ],
+      [
+        64,
+        64
+      ],
+      [
+        64,
+        64
+      ]
+    ],
+    [
+      [
+        64,
+        128
+      ],
+      [
+        128,
+        128
+      ],
+      [
+        128,
+        128
+      ]
+    ]
+  ],
+  "downsampling": "convolution",
+  "dropout": 0.75,
+  "learning_rate": 0.005,
+  "learning_rate_decay_activate": true,
+  "learning_rate_decay_period": 24000,
+  "learning_rate_decay_type": "polynomial",
+  "learning_rate_decay_rate": 0.99,
+  "batch_norm_activate": true,
+  "batch_norm_decay_decay_activate": true,
+  "batch_norm_decay_starting_decay": 0.7,
+  "batch_norm_decay_ending_decay": 0.9,
+  "batch_norm_decay_decay_period": 16000,
+  "weighted_cost-activate": true,
+  "weighted_cost-balanced_activate": true,
+  "weighted_cost-balanced_weights": [
+    1.1,
+    1,
+    1.3
+  ],
+  "weighted_cost-boundaries_sigma": 2,
+  "weighted_cost-boundaries_activate": false,
+  "da-type": "all",
+  "da-0-shifting-activate": true,
+  "da-1-rescaling-activate": false,
+  "da-2-random_rotation-activate": true,
+  "da-3-elastic-activate": true,
+  "da-4-flipping-activate": true,
+  "da-6-reflection_border-activate": false
+}