diff --git a/api.py b/api.py
index e28446ad27ce88ff56f286f8badfa0c42f51dce8..b51364991987556684cd4156ca515b519486a726 100644
--- a/api.py
+++ b/api.py
@@ -6,6 +6,7 @@ from model_server.ilastik import IlastikPixelClassifierModel, IlastikObjectClass
from model_server.model import DummyImageToImageModel, ParameterExpectedError
from model_server.session import Session
from model_server.workflow import infer_image_to_image
+from model_server.workflow_ilastik import infer_px_then_ob_model
app = FastAPI(debug=True)
session = Session()
@@ -62,19 +63,24 @@ def load_ilastik_pixel_classification_model(project_file: str) -> dict:
def load_ilastik_object_classification_model(project_file: str) -> dict:
return load_ilastik_model(IlastikObjectClassifierModel, project_file)
+def validate_workflow_inputs(model_ids, inpaths):
+ for mid in model_ids:
+ if mid not in session.describe_loaded_models().keys():
+ raise HTTPException(
+ status_code=409,
+ detail=f'Model {mid} has not been loaded'
+ )
+ for inpa in inpaths:
+ if not inpa.exists():
+ raise HTTPException(
+ status_code=404,
+ detail=f'Could not find file:\n{inpa}'
+ )
+
@app.put('/infer/from_image_file')
def infer_img(model_id: str, input_filename: str, channel: int = None) -> dict:
- if model_id not in session.describe_loaded_models().keys():
- raise HTTPException(
- status_code=409,
- detail=f'Model {model_id} has not been loaded'
- )
inpath = session.paths['inbound_images'] / input_filename
- if not inpath.exists():
- raise HTTPException(
- status_code=404,
- detail=f'Could not find file:\n{inpath}'
- )
+ validate_workflow_inputs([model_id], [inpath])
record = infer_image_to_image(
inpath,
session.models[model_id]['object'],
@@ -82,4 +88,20 @@ def infer_img(model_id: str, input_filename: str, channel: int = None) -> dict:
channel=channel,
)
session.record_workflow_run(record)
+ return record
+
+@app.put('/models/ilastik/pixel_then_object_classification/infer')
+def infer_px_then_ob_maps(px_model_id: str, ob_model_id: str, input_filename: str, channel: int = None) -> dict:
+ inpath = session.paths['inbound_images'] / input_filename
+ validate_workflow_inputs([px_model_id, ob_model_id], [inpath])
+ try:
+ record = infer_px_then_ob_model(
+ inpath,
+ session.models[px_model_id]['object'],
+ session.models[ob_model_id]['object'],
+ session.paths['outbound_images'],
+ channel=channel
+ )
+ except AssertionError:
+ raise HTTPException(f'Incompatible models {px_model_id} and/or {ob_model_id}')
return record
\ No newline at end of file
diff --git a/model_server/workflow.py b/model_server/workflow.py
index a89f900a95536da22bb3acea88369648fbb7bec8..7c09bc46835eacb04a31871534a91786991267ec 100644
--- a/model_server/workflow.py
+++ b/model_server/workflow.py
@@ -1,11 +1,12 @@
"""
Implementation of image analysis work behind API endpoints, without knowledge of persistent data in server session.
"""
-
+from pathlib import Path
from time import perf_counter
from typing import Dict
from model_server.image import generate_file_accessor, write_accessor_data_to_file
+from model_server.model import Model
from pydantic import BaseModel
@@ -28,7 +29,15 @@ class WorkflowRunRecord(BaseModel):
timer_results: Dict[str, float]
-def infer_image_to_image(fpi, model, where_output, **kwargs) -> dict:
+def infer_image_to_image(fpi: Path, model: Model, where_output: Path, **kwargs) -> WorkflowRunRecord:
+ """
+ Generic workflow where a model processes an input image into an output image
+ :param fpi: Path object that references input image file
+ :param model: model object
+ :param where_output: Path object that references output image directory
+ :param kwargs: variable-length keyword arguments
+ :return: record object
+ """
ti = Timer()
ch = kwargs.get('channel')
img = generate_file_accessor(fpi).get_one_channel_data(ch)
diff --git a/model_server/workflow_ilastik.py b/model_server/workflow_ilastik.py
new file mode 100644
index 0000000000000000000000000000000000000000..db412bb4b9b2ba1e33b0ba42d9d5108bbfcdce5d
--- /dev/null
+++ b/model_server/workflow_ilastik.py
@@ -0,0 +1,73 @@
+"""
+Implementation of image analysis work behind API endpoints, without knowledge of persistent data in server session.
+"""
+from pathlib import Path
+from time import perf_counter
+from typing import Dict
+
+from model_server.ilastik import IlastikPixelClassifierModel, IlastikObjectClassifierModel
+from model_server.image import generate_file_accessor, write_accessor_data_to_file
+from model_server.model import Model
+from model_server.workflow import Timer
+
+from pydantic import BaseModel
+
+class WorkflowRunRecord(BaseModel):
+ pixel_model_id: str
+ object_model_id: str
+ input_filepath: str
+ pixel_map_filepath: str
+ object_map_filepath: str
+ success: bool
+ timer_results: Dict[str, float]
+
+
+def infer_px_then_ob_model(
+ fpi: Path,
+ px_model: IlastikPixelClassifierModel,
+ ob_model: IlastikObjectClassifierModel,
+ where_output: Path,
+ **kwargs
+) -> WorkflowRunRecord:
+ """
+ Workflow that specifically runs an ilastik pixel classifier, then passes results to an object classifier,
+ saving intermediate images
+ :param fpi: Path object that references input image file
+ :param px_model: model instance for pixel classification
+ :param ob_model: model instance for object classification
+ :param where_output: Path object that references output image directory
+ :param kwargs: variable-length keyword arguments
+ :return:
+ """
+ assert isinstance(px_model, IlastikPixelClassifierModel)
+ assert isinstance(ob_model, IlastikObjectClassifierModel)
+
+ ti = Timer()
+ ch = kwargs.get('channel')
+ img = generate_file_accessor(fpi).get_one_channel_data(ch)
+ ti.click('file_input')
+
+ px_map, _ = px_model.infer(img)
+ ti.click('pixel_probability_inference')
+
+ px_map_path = where_output / (px_model.model_id + '_pxmap_' + fpi.stem + '.tif')
+ write_accessor_data_to_file(px_map_path, px_map)
+ ti.click('pixel_map_output')
+
+ ob_map, _ = ob_model.infer(img, px_map)
+ ti.click('object_classification')
+
+ ob_map_path = where_output / (ob_model.model_id + '_obmap_' + fpi.stem + '.tif')
+ write_accessor_data_to_file(ob_map_path, ob_map)
+ ti.click('object_map_output')
+
+ return WorkflowRunRecord(
+ pixel_model_id=px_model.model_id,
+ object_model_id=ob_model.model_id,
+ input_filepath=str(fpi),
+ pixel_map_filepath=str(px_map_path),
+ object_map_filepath=str(ob_map_path),
+ success=True,
+ timer_results=ti.events,
+ )
+
diff --git a/tests/test_ilastik.py b/tests/test_ilastik.py
index 1c55a9a63f4dfd64900e1dd25fdad7800561dee0..25c876b945fdac880f78af76e7e96edb0e4e1cf3 100644
--- a/tests/test_ilastik.py
+++ b/tests/test_ilastik.py
@@ -130,7 +130,6 @@ class TestIlastikOverApi(TestServerBaseClass):
self.assertEqual(resp_list.status_code, 200)
rj = resp_list.json()
self.assertEqual(rj[model_id]['class'], 'IlastikPixelClassifierModel')
-
return model_id
@@ -146,6 +145,7 @@ class TestIlastikOverApi(TestServerBaseClass):
self.assertEqual(resp_list.status_code, 200)
rj = resp_list.json()
self.assertEqual(rj[model_id]['class'], 'IlastikObjectClassifierModel')
+ return model_id
def test_ilastik_infer_pixel_probability(self):
self.copy_input_file_to_server()
@@ -160,3 +160,19 @@ class TestIlastikOverApi(TestServerBaseClass):
},
)
self.assertEqual(resp_infer.status_code, 200, resp_infer.content.decode())
+
+ def test_ilastik_infer_px_then_ob(self):
+ self.copy_input_file_to_server()
+ px_model_id = self.test_load_ilastik_pixel_model()
+ ob_model_id = self.test_load_ilastik_object_model()
+
+ resp_infer = requests.put(
+ self.uri + f'models/ilastik/pixel_then_object_classification/infer/',
+ params={
+ 'px_model_id': px_model_id,
+ 'ob_model_id': ob_model_id,
+ 'input_filename': conf.testing.czifile['filename'],
+ 'channel': 0,
+ }
+ )
+ self.assertEqual(resp_infer.status_code, 200, resp_infer.content.decode())
diff --git a/tests/test_workflow.py b/tests/test_workflow.py
index 9bca0b4af3d440206041ddb16c6c56891a18ed56..6bc8d56d88f960d63cdada4efe68e65c6ecd572f 100644
--- a/tests/test_workflow.py
+++ b/tests/test_workflow.py
@@ -34,6 +34,4 @@ class TestGetSessionObject(unittest.TestCase):
img[0, 0],
0,
'First pixel is not black as expected'
- )
-
- print(result.timer_results)
\ No newline at end of file
+ )
\ No newline at end of file