Renamed ZMask to RoiSet, prototyped object classification methods that add...

Renamed ZMask to RoiSet, prototyped object classification methods that add classification result as a dataframe column

extensions/chaeo/params.py

@@ -2,19 +2,22 @@ from typing import Dict, List, Union
 
 from pydantic import BaseModel
 
+
 class PatchParams(BaseModel):
     draw_bounding_box: bool = False
     draw_contour: bool = False
     draw_mask: bool = False
     rescale_clip: float = 0.001
     focus_metric: str = 'max_sobel'
-    rgb_overlay_channels: List[Union[int, None]] = (None, None, None),
-    rgb_overlay_weights: List[float] = (1.0, 1.0, 1.0)
+    rgb_overlay_channels: List[Union[int, None]] = [None, None, None]
+    rgb_overlay_weights: List[float] = [1.0, 1.0, 1.0]
+
 
 class AnnotatedZStackParams(BaseModel):
     draw_label: bool = False
 
-class ZMaskExportParams(BaseModel):
+
+class RoiSetExportParams(BaseModel):
     pixel_probabilities: bool = False
     patches_3d: Union[PatchParams, None] = None
     patches_2d_for_annotation: Union[PatchParams, None] = None
@@ -22,3 +25,19 @@ class ZMaskExportParams(BaseModel):
     patch_masks: bool = False
     annotated_z_stack: Union[AnnotatedZStackParams, None] = None
 
+
+class RoiClassifierValue(BaseModel):
+    name: str
+    value: int
+
+
+class RoiFilterRange(BaseModel):
+    min: float
+    max: float
+
+
+class RoiFilter(BaseModel):
+    area: Union[RoiFilterRange, None] = None
+    solidity: Union[RoiFilterRange, None] = None
+    classifiers: List[RoiClassifierValue] = []
+

extensions/chaeo/workflows.py

@@ -15,7 +15,7 @@ from extensions.chaeo.models import PatchStackObjectClassifier
 from extensions.chaeo.params import ZMaskExportParams
 from extensions.chaeo.process import mask_largest_object
 from extensions.chaeo.products import export_patches_from_zstack, export_patch_masks_from_zstack, export_multichannel_patches_from_zstack, get_patches_from_zmask_meta, get_patch_masks_from_zmask_meta
-from extensions.chaeo.zmask import project_stack_from_focal_points, ZMaskObjectTable
+from extensions.chaeo.zmask import project_stack_from_focal_points, RoiSet
 from extensions.ilastik.models import IlastikPixelClassifierModel
 
 from model_server.accessors import generate_file_accessor, InMemoryDataAccessor, write_accessor_data_to_file
@@ -281,7 +281,7 @@ def infer_object_map_from_zstack(
     ti.click('threshold_pixel_mask')
 
     # make zmask
-    obj_table = ZMaskObjectTable(
+    obj_table = RoiSet(
         obmask.get_one_channel_data(pxmap_foreground_channel),
         stack.get_one_channel_data(segmentation_channel),
         mask_type=zmask_type,

extensions/chaeo/zmask.py

@@ -9,12 +9,12 @@ from sklearn.linear_model import LinearRegression
 
 from extensions.chaeo.annotators import draw_boxes_on_3d_image
 from extensions.chaeo.products import export_patches_from_zstack, export_multichannel_patches_from_zstack, export_patch_masks_from_zstack
-from extensions.chaeo.params import ZMaskExportParams
+from extensions.chaeo.params import RoiFilter, RoiSetExportParams
 from model_server.accessors import GenericImageDataAccessor, InMemoryDataAccessor, write_accessor_data_to_file
 
 
 
-class ZMaskObjectTable(object):
+class RoiSet(object):
 
     def __init__(
             self,
@@ -41,7 +41,7 @@ class ZMaskObjectTable(object):
     def get_argmax(self):
         return self.interm.argmax
 
-    def export_3d_patches(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_3d_patches(self, where, prefix, channel, params: RoiSetExportParams):
         if not self.count:
             return
         files = export_patches_from_zstack(
@@ -54,7 +54,7 @@ class ZMaskObjectTable(object):
             make_3d=True,
         )
 
-    def export_2d_patches_for_annotation(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_2d_patches_for_annotation(self, where, prefix, channel, params: RoiSetExportParams):
         if not self.count:
             return
         files = export_multichannel_patches_from_zstack(
@@ -78,7 +78,7 @@ class ZMaskObjectTable(object):
         self.df = pd.merge(self.df, df_patches, left_index=True, right_on='df_index').drop(columns='df_index')
         self.df['patch_id'] = self.df.apply(lambda _: uuid4(), axis=1)
 
-    def export_2d_patches_for_training(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_2d_patches_for_training(self, where, prefix, channel, params: RoiSetExportParams):
         if not self.count:
             return
         files = export_multichannel_patches_from_zstack(
@@ -102,7 +102,7 @@ class ZMaskObjectTable(object):
         self.df = pd.merge(self.df, df_patches, left_index=True, right_on='df_index').drop(columns='df_index')
         self.df['patch_id'] = self.df.apply(lambda _: uuid4(), axis=1)
 
-    def export_2d_patches_for_annotation(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_2d_patches_for_annotation(self, where, prefix, channel, params: RoiSetExportParams):
         if not self.count:
             return
         files = export_multichannel_patches_from_zstack(
@@ -115,7 +115,7 @@ class ZMaskObjectTable(object):
             focus_metric=params.focus_metric,
         )
 
-    def export_patch_masks(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_patch_masks(self, where, prefix, channel, params: RoiSetExportParams):
         if not self.count:
             return
         files = export_patch_masks_from_zstack(
@@ -125,7 +125,7 @@ class ZMaskObjectTable(object):
             prefix=prefix,
         )
 
-    def export_annotated_zstack(self, where, prefix, channel, params: ZMaskExportParams):
+    def export_annotated_zstack(self, where, prefix, channel, params: RoiSetExportParams):
         annotated = InMemoryDataAccessor(
             draw_boxes_on_3d_image(
                 self.acc_raw.get_one_channel_data(channel).data,
@@ -152,6 +152,19 @@ class ZMaskObjectTable(object):
             projected = self.acc_raw.data.max(axis=-1)
         return projected
 
+    def classify_by(self, column_name, object_classification_model, patch_basis=True):
+        # add one column to df where each value is an integer
+        pass
+
+    def get_raw_patches(self, filters: RoiFilter):
+        pass
+
+    def get_patch_masks(self, filters: RoiFilter):
+        pass
+
+    def get_object_map(self, filters: RoiFilter):
+        pass
+
 def build_zmask_from_object_mask(
         obmask: GenericImageDataAccessor,
         zstack: GenericImageDataAccessor,