From b9037651b97dd8ddd58f985db2fdb260fd2e72b4 Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Fri, 26 Apr 2024 15:05:13 +0200
Subject: [PATCH] Test coverage of ilastik workflow and API endpoint that
currently restricts multichannel inputs
---
.../extensions/ilastik/tests/test_ilastik.py | 58 ++++++++++++++++---
1 file changed, 50 insertions(+), 8 deletions(-)
diff --git a/model_server/extensions/ilastik/tests/test_ilastik.py b/model_server/extensions/ilastik/tests/test_ilastik.py
index d98a41eb..2406cdbe 100644
--- a/model_server/extensions/ilastik/tests/test_ilastik.py
+++ b/model_server/extensions/ilastik/tests/test_ilastik.py
@@ -7,6 +7,7 @@ import numpy as np
from model_server.conf.testing import czifile, ilastik_classifiers, output_path, roiset_test_data
from model_server.base.accessors import CziImageFileAccessor, generate_file_accessor, InMemoryDataAccessor, PatchStack, write_accessor_data_to_file
from model_server.extensions.ilastik import models as ilm
+from model_server.extensions.ilastik.workflows import infer_px_then_ob_model
from model_server.base.models import InvalidObjectLabelsError
from model_server.base.roiset import _get_label_ids, RoiSet, RoiSetMetaParams
from model_server.base.workflows import classify_pixels
@@ -325,7 +326,7 @@ class TestIlastikOnMultichannelInputs(TestServerBaseClass):
super(TestIlastikOnMultichannelInputs, self).setUp()
self.pa_px_classifier = ilastik_classifiers['px_color_zstack']
self.pa_ob_classifier = ilastik_classifiers['ob_color_zstack']
- self.input_image = generate_file_accessor(roiset_test_data['multichannel_zstack']['path'])
+ self.pa_input_image = roiset_test_data['multichannel_zstack']['path']
def _copy_input_file_to_server(self):
from shutil import copyfile
@@ -340,21 +341,62 @@ class TestIlastikOnMultichannelInputs(TestServerBaseClass):
)
def test_classify_pixels(self):
- self.assertGreater(self.input_image.chroma, 1)
+ img = generate_file_accessor(self.pa_input_image)
+ self.assertGreater(img.chroma, 1)
mod = ilm.IlastikPixelClassifierModel(params={'project_file': self.pa_px_classifier})
- pxmap = mod.infer(self.input_image)[0]
- self.assertEqual(pxmap.hw, self.input_image.hw)
- self.assertEqual(pxmap.nz, self.input_image.nz)
+ pxmap = mod.infer(img)[0]
+ self.assertEqual(pxmap.hw, img.hw)
+ self.assertEqual(pxmap.nz, img.nz)
return pxmap
def test_classify_objects(self):
pxmap = self.test_classify_pixels()
+ img = generate_file_accessor(self.pa_input_image)
mod = ilm.IlastikObjectClassifierFromPixelPredictionsModel(params={'project_file': self.pa_ob_classifier})
- obmap = mod.infer(self.input_image, pxmap)[0]
- self.assertEqual(obmap.hw, self.input_image.hw)
- self.assertEqual(obmap.nz, self.input_image.nz)
+ obmap = mod.infer(img, pxmap)[0]
+ self.assertEqual(obmap.hw, img.hw)
+ self.assertEqual(obmap.nz, img.nz)
+
+ def _call_workflow(self, channel):
+ return infer_px_then_ob_model(
+ self.pa_input_image,
+ ilm.IlastikPixelClassifierModel(params={'project_file': self.pa_px_classifier}),
+ ilm.IlastikObjectClassifierFromPixelPredictionsModel(params={'project_file': self.pa_ob_classifier}),
+ output_path,
+ channel=channel,
+ )
+
+ def test_workflow(self):
+ with self.assertRaises(ilm.IlastikInputShapeError):
+ self._call_workflow(channel=0)
+
+ res = self._call_workflow(channel=None)
+ def test_api(self):
+ resp_load = self._put(
+ 'ilastik/seg/load/',
+ query={'project_file': str(self.pa_px_classifier)},
+ )
+ self.assertEqual(resp_load.status_code, 200, resp_load.json())
+ px_model_id = resp_load.json()['model_id']
+
+ resp_load = self._put(
+ 'ilastik/pxmap_to_obj/load/',
+ query={'project_file': str(self.pa_ob_classifier)},
+ )
+ self.assertEqual(resp_load.status_code, 200, resp_load.json())
+ ob_model_id = resp_load.json()['model_id']
+ resp_infer = self._put(
+ 'ilastik/pixel_then_object_classification/infer/',
+ query={
+ 'px_model_id': px_model_id,
+ 'ob_model_id': ob_model_id,
+ 'input_filename': self.pa_input_image,
+ # 'channel': 0,
+ }
+ )
+ self.assertEqual(resp_infer.status_code, 200, resp_infer.content.decode())
class TestIlastikObjectClassification(unittest.TestCase):
--
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