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/api.py

@@ -22,6 +22,21 @@ def read_root():
     return {'success': True}
 
 
+@app.get('/paths/session')
+def get_top_session_path():
+    return session.get_paths()['session']
+
+
+@app.get('/paths/inbound')
+def get_inbound_path():
+    return session.get_paths()['inbound_images']
+
+
+@app.get('/paths/outbound')
+def get_outbound_path():
+    return session.get_paths()['outbound_images']
+
+
 @app.get('/paths')
 def list_session_paths():
     return session.get_paths()