diff --git a/extensions/ilastik/tests/test_ilastik.py b/extensions/ilastik/tests/test_ilastik.py
index 1dfbde1685218234f152ace5968a1aae4a8a9fff..5881679b98ee1bdf7b0013250862eabce2d99cbb 100644
--- a/extensions/ilastik/tests/test_ilastik.py
+++ b/extensions/ilastik/tests/test_ilastik.py
@@ -7,7 +7,7 @@ import numpy as np
from conf.testing import czifile, ilastik_classifiers, output_path
from model_server.accessors import CziImageFileAccessor, InMemoryDataAccessor, write_accessor_data_to_file
from extensions.ilastik import models as ilm
-from model_server.workflows import infer_image_to_image
+from model_server.workflows import classify_pixels
from tests.test_api import TestServerBaseClass
class TestIlastikPixelClassification(unittest.TestCase):
@@ -115,7 +115,7 @@ class TestIlastikPixelClassification(unittest.TestCase):
self.assertEqual(objmap.data.max(), 3)
def test_ilastik_pixel_classification_as_workflow(self):
- result = infer_image_to_image(
+ result = classify_pixels(
czifile['path'],
ilm.IlastikPixelClassifierModel(
{'project_file': ilastik_classifiers['px']}
@@ -243,7 +243,7 @@ class TestIlastikOverApi(TestServerBaseClass):
model_id = self.test_load_ilastik_pixel_model()
resp_infer = requests.put(
- self.uri + f'infer/from_image_file',
+ self.uri + f'workflows/segment',
params={
'model_id': model_id,
'input_filename': czifile['filename'],
diff --git a/model_server/api.py b/model_server/api.py
index bc9a57fe79288c2f63ebf79e055bf5785be2f823..a1c785313881d594e49fa8f335f24664e4429bf2 100644
--- a/model_server/api.py
+++ b/model_server/api.py
@@ -1,9 +1,9 @@
from fastapi import FastAPI, HTTPException
-from model_server.models import DummyImageToImageModel
+from model_server.models import DummySegmentationModel
from model_server.session import Session, InvalidPathError
from model_server.validators import validate_workflow_inputs
-from model_server.workflows import infer_image_to_image
+from model_server.workflows import classify_pixels
from extensions.ilastik.workflows import infer_px_then_ob_model
app = FastAPI(debug=True)
@@ -67,13 +67,13 @@ def list_active_models():
@app.put('/models/dummy/load/')
def load_dummy_model() -> dict:
- return {'model_id': session.load_model(DummyImageToImageModel)}
+ return {'model_id': session.load_model(DummySegmentationModel)}
-@app.put('/infer/from_image_file')
+@app.put('/workflows/segment')
def infer_img(model_id: str, input_filename: str, channel: int = None) -> dict:
inpath = session.paths['inbound_images'] / input_filename
validate_workflow_inputs([model_id], [inpath])
- record = infer_image_to_image(
+ record = classify_pixels(
inpath,
session.models[model_id]['object'],
session.paths['outbound_images'],
diff --git a/model_server/models.py b/model_server/models.py
index 4f07da5730a3d06d93f6a310bafead67f740a202..f0864147279dbef501138307ae885a742d390757 100644
--- a/model_server/models.py
+++ b/model_server/models.py
@@ -91,7 +91,7 @@ class InstanceSegmentationModel(ImageToImageModel):
-class DummyImageToImageModel(ImageToImageModel):
+class DummySegmentationModel(SemanticSegmentationModel):
model_id = 'dummy_make_white_square'
@@ -106,6 +106,11 @@ class DummyImageToImageModel(ImageToImageModel):
result[floor(0.25 * h) : floor(0.75 * h), floor(0.25 * w) : floor(0.75 * w)] = 255
return InMemoryDataAccessor(data=result), {'success': True}
+ def label_pixel_class(
+ self, img: GenericImageDataAccessor, **kwargs) -> GenericImageDataAccessor:
+ mask, _ = self.infer(img)
+ return mask
+
class Error(Exception):
pass
diff --git a/model_server/workflows.py b/model_server/workflows.py
index 6eb7b50d1b6e78518cc500ac5c1936cd266a333b..9c6da2142ff557fdaf5d0cb521169f03816eb512 100644
--- a/model_server/workflows.py
+++ b/model_server/workflows.py
@@ -6,7 +6,7 @@ from time import perf_counter
from typing import Dict
from model_server.accessors import generate_file_accessor, write_accessor_data_to_file
-from model_server.models import Model
+from model_server.models import SemanticSegmentationModel
from pydantic import BaseModel
@@ -29,11 +29,12 @@ class WorkflowRunRecord(BaseModel):
timer_results: Dict[str, float]
-def infer_image_to_image(fpi: Path, model: Model, where_output: Path, **kwargs) -> WorkflowRunRecord:
+def classify_pixels(fpi: Path, model: SemanticSegmentationModel, where_output: Path, **kwargs) -> WorkflowRunRecord:
"""
- Generic workflow where a model processes an input image into an output image
+ Run a semantic segmentation model to compute a binary mask from an input image
+
:param fpi: Path object that references input image file
- :param model: model object
+ :param model: semantic segmentation model instance
:param where_output: Path object that references output image directory
:param kwargs: variable-length keyword arguments
:return: record object
diff --git a/tests/test_api.py b/tests/test_api.py
index e6c0f7997ea1a6396d30530d964f40cb7213fbe6..e846be74218912a97b346d862bdce4850c0eb733 100644
--- a/tests/test_api.py
+++ b/tests/test_api.py
@@ -4,7 +4,7 @@ import requests
import unittest
from conf.testing import czifile
-from model_server.models import DummyImageToImageModel
+from model_server.models import DummySegmentationModel
class TestServerBaseClass(unittest.TestCase):
def setUp(self) -> None:
@@ -70,7 +70,7 @@ class TestApiFromAutomatedClient(TestServerBaseClass):
resp_list = requests.get(self.uri + 'models')
self.assertEqual(resp_list.status_code, 200)
rj = resp_list.json()
- self.assertEqual(rj[model_id]['class'], 'DummyImageToImageModel')
+ self.assertEqual(rj[model_id]['class'], 'DummySegmentationModel')
return model_id
def test_respond_with_error_when_invalid_filepath_requested(self):
@@ -89,7 +89,7 @@ class TestApiFromAutomatedClient(TestServerBaseClass):
def test_i2i_inference_errors_when_model_not_found(self):
model_id = 'not_a_real_model'
resp = requests.put(
- self.uri + f'infer/from_image_file',
+ self.uri + f'workflows/segment',
params={
'model_id': model_id,
'input_filename': 'not_a_real_file.name'
@@ -101,7 +101,7 @@ class TestApiFromAutomatedClient(TestServerBaseClass):
model_id = self.test_load_dummy_model()
self.copy_input_file_to_server()
resp_infer = requests.put(
- self.uri + f'infer/from_image_file',
+ self.uri + f'workflows/segment',
params={
'model_id': model_id,
'input_filename': czifile['filename'],
diff --git a/tests/test_model.py b/tests/test_model.py
index 661aeadf93825afc430e55f56326def0fe3f43b0..0d5f98aea4aee70da25ef3edf71b36eebac01a3e 100644
--- a/tests/test_model.py
+++ b/tests/test_model.py
@@ -1,22 +1,22 @@
import unittest
from conf.testing import czifile
from model_server.accessors import CziImageFileAccessor
-from model_server.models import DummyImageToImageModel, CouldNotLoadModelError
+from model_server.models import DummySegmentationModel, CouldNotLoadModelError
class TestCziImageFileAccess(unittest.TestCase):
def setUp(self) -> None:
self.cf = CziImageFileAccessor(czifile['path'])
def test_instantiate_model(self):
- model = DummyImageToImageModel(params=None)
+ model = DummySegmentationModel(params=None)
self.assertTrue(model.loaded)
def test_instantiate_model_with_nondefault_kwarg(self):
- model = DummyImageToImageModel(autoload=False)
+ model = DummySegmentationModel(autoload=False)
self.assertFalse(model.autoload, 'Could not override autoload flag in subclass of Model.')
def test_raise_error_if_cannot_load_model(self):
- class UnloadableDummyImageToImageModel(DummyImageToImageModel):
+ class UnloadableDummyImageToImageModel(DummySegmentationModel):
def load(self):
return False
@@ -24,7 +24,7 @@ class TestCziImageFileAccess(unittest.TestCase):
mi = UnloadableDummyImageToImageModel()
def test_czifile_is_correct_shape(self):
- model = DummyImageToImageModel()
+ model = DummySegmentationModel()
img, _ = model.infer(self.cf)
w = czifile['w']
diff --git a/tests/test_workflow.py b/tests/test_workflow.py
index 2cab499d04c222651894d9064c1f7f990050d626..a88d8791eb4cba9ce6544124e51edacfa3a79c0a 100644
--- a/tests/test_workflow.py
+++ b/tests/test_workflow.py
@@ -1,16 +1,16 @@
import unittest
from conf.testing import czifile, output_path
-from model_server.models import DummyImageToImageModel
-from model_server.workflows import infer_image_to_image
+from model_server.models import DummySegmentationModel
+from model_server.workflows import classify_pixels
class TestGetSessionObject(unittest.TestCase):
def setUp(self) -> None:
- self.model = DummyImageToImageModel()
+ self.model = DummySegmentationModel()
def test_single_session_instance(self):
- result = infer_image_to_image(czifile['path'], self.model, output_path, channel=2)
+ result = classify_pixels(czifile['path'], self.model, output_path, channel=2)
self.assertTrue(result.success)
import tifffile