Updates for TREC pipelines

Changes supporting use of pipelines in trec-adaptive-feedback project:

• generally, accessors' and models' IDs can be set with respective argument
• test client methods now handle response success check and variable parsing
• implemented functional threshold segmentation and (in base.roiset) classification models; threshold is relative to dataset full range (0.0 to 1.0)
• consequently, more tests cover base package without dependency on ilastik
• RoiSet returned by pipelines get IDs and are registered in server session, accesible at respective endpoints
• Pydantic models only used by FastAPI now; underlying model, accessor, and pipeline functions should interact with python objects and parameter dictionaries only
• RoiSet filters also include minimal and diagonal height, width dimension; are applied before time-intensity pixel array operations to increase performance
• performance improvement when passing patch stacks to ilastik pixel classifier
• RoiSet.classify_by can optionally filter by additional classification columns, e.g. to implement intensity gating

model_server/base/accessors.py

@@ -451,6 +451,14 @@ class PatchStack(InMemoryDataAccessor):
         else:
             return self.data[:, :, :, 0, :]
 
+    @property
+    def smallest(self):
+        return np.array([p.shape for p in self.get_list()]).min(axis=0),
+
+    @property
+    def largest(self):
+        return np.array([p.shape for p in self.get_list()]).max(axis=0)
+
     def export_pyxcz(self, fpath: Path):
         tzcyx = np.moveaxis(
             self.pyxcz,  # yxcz