copy code from old PR

Author: Jiaqi-Lv

docs/pretrained.rst

@@ -353,7 +353,7 @@ The input output configuration is as follows:
         ioconfig = IOPatchPredictorConfig(
             patch_input_shape=(31, 31),
             stride_shape=(8, 8),
-            input_resolutions=[{"resolution": 0.25, "units": "mpp"}]
+            input_resolutions=[{"resolution": 0.5, "units": "mpp"}]
         )
 
 
@@ -369,7 +369,7 @@ The input output configuration is as follows:
         ioconfig = IOPatchPredictorConfig(
             patch_input_shape=(252, 252),
             stride_shape=(150, 150),
-            input_resolutions=[{"resolution": 0.25, "units": "mpp"}]
+            input_resolutions=[{"resolution": 0.5, "units": "mpp"}]
         )
 
 
@@ -393,7 +393,7 @@ The input output configuration is as follows:
         ioconfig = IOPatchPredictorConfig(
             patch_input_shape=(31, 31),
             stride_shape=(8, 8),
-            input_resolutions=[{"resolution": 0.25, "units": "mpp"}]
+            input_resolutions=[{"resolution": 0.5, "units": "mpp"}]
         )
 
 
@@ -409,7 +409,7 @@ The input output configuration is as follows:
         ioconfig = IOPatchPredictorConfig(
             patch_input_shape=(252, 252),
             stride_shape=(150, 150),
-            input_resolutions=[{"resolution": 0.25, "units": "mpp"}]
+            input_resolutions=[{"resolution": 0.5, "units": "mpp"}]
         )
 
 

tests/engines/test_nucleus_detection_engine.py

@@ -0,0 +1,67 @@
+"""Tests for NucleusDetector."""
+
+import pathlib
+import shutil
+
+import pandas as pd
+import pytest
+
+from tiatoolbox.models.engine.nucleus_detector import (
+    IONucleusDetectorConfig,
+    NucleusDetector,
+)
+from tiatoolbox.utils import env_detection as toolbox_env
+
+ON_GPU = not toolbox_env.running_on_ci() and toolbox_env.has_gpu()
+
+
+def _rm_dir(path):
+    """Helper func to remove directory."""
+    if pathlib.Path(path).exists():
+        shutil.rmtree(path, ignore_errors=True)
+
+
+def check_output(path):
+    """Check NucleusDetector output."""
+    coordinates = pd.read_csv(path)
+    assert coordinates.x[0] == pytest.approx(53, abs=2)
+    assert coordinates.x[1] == pytest.approx(55, abs=2)
+    assert coordinates.y[0] == pytest.approx(107, abs=2)
+    assert coordinates.y[1] == pytest.approx(127, abs=2)
+
+
+def test_nucleus_detector_engine(remote_sample, tmp_path):
+    """Test for nucleus detection engine."""
+    mini_wsi_svs = pathlib.Path(remote_sample("wsi4_512_512_svs"))
+
+    nucleus_detector = NucleusDetector(pretrained_model="mapde-conic")
+    _ = nucleus_detector.predict(
+        [mini_wsi_svs],
+        mode="wsi",
+        save_dir=tmp_path / "output",
+        on_gpu=ON_GPU,
+    )
+
+    check_output(tmp_path / "output" / "0.locations.0.csv")
+
+    _rm_dir(tmp_path / "output")
+
+    ioconfig = IONucleusDetectorConfig(
+        input_resolutions=[{"units": "mpp", "resolution": 0.5}],
+        output_resolutions=[{"units": "mpp", "resolution": 0.5}],
+        save_resolution=None,
+        patch_input_shape=[252, 252],
+        patch_output_shape=[252, 252],
+        stride_shape=[150, 150],
+    )
+
+    nucleus_detector = NucleusDetector(pretrained_model="mapde-conic")
+    _ = nucleus_detector.predict(
+        [mini_wsi_svs],
+        mode="wsi",
+        save_dir=tmp_path / "output",
+        on_gpu=ON_GPU,
+        ioconfig=ioconfig,
+    )
+
+    check_output(tmp_path / "output" / "0.locations.0.csv")

tiatoolbox/data/pretrained_model.yaml

@@ -815,7 +815,7 @@ mapde-crchisto:
             threshold_abs: 250
             num_classes: 1
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - { "units": "mpp", "resolution": 0.5 }
@@ -837,7 +837,7 @@ mapde-conic:
             threshold_abs: 205
             num_classes: 1
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - { "units": "mpp", "resolution": 0.5 }
@@ -860,7 +860,7 @@ sccnn-crchisto:
             threshold_abs: 0.20
             patch_output_shape: [ 13, 13 ]
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - { "units": "mpp", "resolution": 0.5 }
@@ -883,7 +883,7 @@ sccnn-conic:
             threshold_abs: 0.05
             patch_output_shape: [ 13, 13 ]
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - { "units": "mpp", "resolution": 0.5 }
@@ -903,7 +903,7 @@ nuclick_original-pannuke:
             num_input_channels: 5
             num_output_channels: 1
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - {'units': 'baseline', 'resolution': 0.25}
@@ -925,7 +925,7 @@ nuclick_light-pannuke:
             decoder_block: [3,3]
             skip_type: "add"
     ioconfig:
-        class: semantic_segmentor.IOSegmentorConfig
+        class: io_config.IOSegmentorConfig
         kwargs:
             input_resolutions:
                 - {'units': 'baseline', 'resolution': 0.25}

tiatoolbox/models/engine/__init__.py

@@ -2,13 +2,15 @@
 
 from . import (
     engine_abc,
+    nucleus_detector,
     nucleus_instance_segmentor,
     patch_predictor,
     semantic_segmentor,
 )
 
 __all__ = [
     "engine_abc",
+    "nucleus_detector",
     "nucleus_instance_segmentor",
     "patch_predictor",
     "semantic_segmentor",