Merge pull request #139 from computational-cell-analytics/model-fixes

Fix mitochondria2 model and add proper model test

Author: constantinpape

synapse_net/inference/inference.py

@@ -112,6 +112,8 @@ def get_model_training_resolution(model_type: str) -> Dict[str, float]:
         "active_zone": {"x": 1.38, "y": 1.38, "z": 1.38},
         "compartments": {"x": 3.47, "y": 3.47, "z": 3.47},
         "mitochondria": {"x": 2.07, "y": 2.07, "z": 2.07},
+        # TODO: this is just copied from the previous mito model, it may be necessary to update this.
+        "mitochondria2": {"x": 2.07, "y": 2.07, "z": 2.07},
         "cristae": {"x": 1.44, "y": 1.44, "z": 1.44},
         "ribbon": {"x": 1.188, "y": 1.188, "z": 1.188},
         "vesicles_2d": {"x": 1.35, "y": 1.35},

test/test_inference.py

@@ -4,6 +4,7 @@
 from shutil import rmtree
 
 import imageio.v3 as imageio
+import requests
 from synapse_net.file_utils import read_mrc
 from synapse_net.sample_data import get_sample_data
 
@@ -23,6 +24,26 @@ def tearDown(self):
         except OSError:
             pass
 
+    # Test that all models can be accessed by pooch and have the necessary resolution information.
+    def test_models(self):
+        from synapse_net.inference.inference import _get_model_registry, get_model_training_resolution
+
+        def check_url(url):
+            try:
+                # Make a HEAD request to the URL, which fetches HTTP headers but no content.
+                response = requests.head(url, allow_redirects=True)
+                # Check if the HTTP status code is one that indicates availability (200 <= code < 400).
+                return response.status_code < 400
+            except requests.RequestException:
+                # Handle connection exceptions
+                return False
+
+        registry = _get_model_registry()
+        for name in registry.registry.keys():
+            url_exists = check_url(registry.get_url(name))
+            self.assertTrue(url_exists)
+            get_model_training_resolution(name)
+
     def test_run_segmentation(self):
         from synapse_net.inference import run_segmentation, get_model