Add model and other files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+nested.h5 filter=lfs diff=lfs merge=lfs -text

.idea/.gitignore

@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/NeuroNest3D.iml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

@@ -0,0 +1,27 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="DuplicatedCode" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <Languages>
+        <language minSize="89" name="Python" />
+      </Languages>
+    </inspection_tool>
+    <inspection_tool class="Eslint" enabled="true" level="WARNING" enabled_by_default="true" />
+    <inspection_tool class="PyPep8NamingInspection" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <option name="ignoredErrors">
+        <list>
+          <option value="N806" />
+        </list>
+      </option>
+    </inspection_tool>
+    <inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredIdentifiers">
+        <list>
+          <option value="map.__getitem__" />
+          <option value="cv2.drawMarker" />
+          <option value="cv2.putText" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (YoutubeData)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/NeuroNest3D.iml" filepath="$PROJECT_DIR$/.idea/NeuroNest3D.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

logs/tensorboard/events.out.tfevents.1705017197.96cb84ca1a73.804.0.v2

@@ -0,0 +1,3 @@
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+oid sha256:2ffe4987ba065e9bd085909fc9b6040866d01663305e60c40e3cf5aed05ae4b6
+size 52046

logs/training.log

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loss.py

@@ -0,0 +1,57 @@
+import keras.backend as K
+
+# dice loss as defined above for 4 classes
+def dice_coef(y_true, y_pred, smooth=1.0):
+    class_num = 4
+    for i in range(class_num):
+        y_true_f = K.flatten(y_true[:,:,:,i])
+        y_pred_f = K.flatten(y_pred[:,:,:,i])
+        intersection = K.sum(y_true_f * y_pred_f)
+        loss = ((2. * intersection + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth))
+   #     K.print_tensor(loss, message='loss value for class {} : '.format(SEGMENT_CLASSES[i]))
+        if i == 0:
+            total_loss = loss
+        else:
+            total_loss = total_loss + loss
+    total_loss = total_loss / class_num
+#    K.print_tensor(total_loss, message=' total dice coef: ')
+    return total_loss
+
+
+
+# define per class evaluation of dice coef
+# inspired by https://github.com/keras-team/keras/issues/9395
+def dice_coef_necrotic(y_true, y_pred, epsilon=1e-6):
+    intersection = K.sum(K.abs(y_true[:,:,:,1] * y_pred[:,:,:,1]))
+    return (2. * intersection) / (K.sum(K.square(y_true[:,:,:,1])) + K.sum(K.square(y_pred[:,:,:,1])) + epsilon)
+
+def dice_coef_edema(y_true, y_pred, epsilon=1e-6):
+    intersection = K.sum(K.abs(y_true[:,:,:,2] * y_pred[:,:,:,2]))
+    return (2. * intersection) / (K.sum(K.square(y_true[:,:,:,2])) + K.sum(K.square(y_pred[:,:,:,2])) + epsilon)
+
+def dice_coef_enhancing(y_true, y_pred, epsilon=1e-6):
+    intersection = K.sum(K.abs(y_true[:,:,:,3] * y_pred[:,:,:,3]))
+    return (2. * intersection) / (K.sum(K.square(y_true[:,:,:,3])) + K.sum(K.square(y_pred[:,:,:,3])) + epsilon)
+
+
+
+# Computing Precision
+def precision(y_true, y_pred):
+        true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
+        predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))
+        precision = true_positives / (predicted_positives + K.epsilon())
+        return precision
+
+
+# Computing Sensitivity
+def sensitivity(y_true, y_pred):
+    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
+    possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))
+    return true_positives / (possible_positives + K.epsilon())
+
+
+# Computing Specificity
+def specificity(y_true, y_pred):
+    true_negatives = K.sum(K.round(K.clip((1-y_true) * (1-y_pred), 0, 1)))
+    possible_negatives = K.sum(K.round(K.clip(1-y_true, 0, 1)))
+    return true_negatives / (possible_negatives + K.epsilon())

main.py

@@ -0,0 +1,18 @@
+from huggingface_hub import push_to_hub_keras
+from loss import *
+import keras
+import tensorflow as tf
+
+# Load the model
+model = keras.models.load_model('nested.h5',
+                                custom_objects={'accuracy': tf.keras.metrics.MeanIoU(num_classes=4),
+                                                "dice_coef": dice_coef,
+                                                "precision": precision,
+                                                "sensitivity": sensitivity,
+                                                "specificity": specificity,
+                                                "dice_coef_necrotic": dice_coef_necrotic,
+                                                "dice_coef_edema": dice_coef_edema,
+                                                "dice_coef_enhancing": dice_coef_enhancing
+                                                },
+                                compile=False
+                                )

nested.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c38c136bca9526cdd79268fbf8291d260fcb40238cd3424c8e3b290aa3e94243
+size 93325760