Add tests for image layer, image plane, inventory, saved layout, commands, documentation, manifest, and packaging

- Implement tests for image layer functionality including alpha curve and depth layer behavior.
- Create tests for image plane evaluation and modifier input handling.
- Add tests to verify the saved asset inventory and its persistence.
- Introduce tests for the documentation command to ensure correct project version deployment.
- Validate the extension manifest structure and required permissions.
- Develop tests for the packaging process, ensuring correct platform handling and dependency management.
- Enhance image depth plane group functionality with new split threshold input and surface processing.

tests/anyimage/server/test_model_ben2_onnx.py

@@ -0,0 +1,70 @@
+import unittest
+from types import SimpleNamespace
+from unittest.mock import patch
+import numpy as np
+from PIL import Image
+
+
+from server.models import onnx_ben2
+
+
+class FakeSession:
+    def get_providers(self):
+        return ["CPUExecutionProvider"]
+
+    def get_inputs(self):
+        return [SimpleNamespace(name="input")]
+
+    def get_outputs(self):
+        return [SimpleNamespace(name="alpha")]
+
+    def run(self, output_names, feeds):
+        self.output_names = output_names
+        self.feeds = feeds
+        gradient = np.linspace(0.0, 1.0, 1024, dtype=np.float32)
+        return [np.tile(gradient, (1024, 1))[None, None]]
+
+
+class Ben2OnnxTest(unittest.TestCase):
+    def test_infer_forwards_memory_release_boundary(self):
+        session = FakeSession()
+
+        with patch.object(
+            onnx_ben2,
+            "run_session",
+            side_effect=lambda model, names, feeds, **_options: model.run(
+                names, feeds
+            ),
+        ) as run:
+            result = onnx_ben2.infer(
+                session,
+                Image.new("RGB", (40, 20)),
+                release_memory=False,
+            )
+
+        self.assertEqual(result.size, (40, 20))
+        self.assertFalse(run.call_args.kwargs["release_memory"])
+
+    def test_preprocess_matches_model_layout(self):
+        image = Image.new("RGB", (40, 20), (64, 128, 192))
+        result = onnx_ben2.preprocess(image)
+
+        self.assertEqual(result.shape, (1, 3, 1024, 1024))
+        self.assertEqual(result.dtype, np.float32)
+        self.assertTrue(result.flags.c_contiguous)
+
+    def test_infer_restores_original_size_and_alpha(self):
+        session = FakeSession()
+        image = Image.new("RGB", (40, 20), (10, 20, 30))
+
+        result = onnx_ben2.infer(session, image)
+
+        self.assertEqual(result.mode, "RGBA")
+        self.assertEqual(result.size, image.size)
+        self.assertEqual(session.feeds["input"].shape, (1, 3, 1024, 1024))
+        alpha = np.asarray(result.getchannel("A"))
+        self.assertLess(int(alpha[:, 0].max()), int(alpha[:, -1].min()))
+
+
+if __name__ == "__main__":
+    unittest.main()