Add comprehensive tests for ONNX models and server jobs

- Introduced tests for the Moge3 ONNX model, including input validation, inference, and caching mechanisms.
- Added tests for ONNX runtime configurations and session management.
- Implemented tests for image upscaling functionality using ONNX models, ensuring proper handling of alpha channels and memory management.
- Created tests for panorama generation, verifying depth and visibility metrics.
- Developed tests for prediction artifacts, ensuring correct depth and normal data handling.
- Added server job tests for background removal and depth plane geometry generation, validating input handling and output correctness.
- Included environment tests to ensure proper dependency management and CI configurations.

tests/ai/test_model_upscale_onnx.py

@@ -0,0 +1,164 @@
+import unittest
+from types import SimpleNamespace
+from unittest.mock import patch
+import numpy as np
+from PIL import Image
+
+
+from server.models import onnx_upscale
+
+
+class FakeSession:
+    def get_providers(self):
+        return ["CPUExecutionProvider"]
+
+    def get_inputs(self):
+        return [SimpleNamespace(name="input")]
+
+    def get_outputs(self):
+        return [SimpleNamespace(name="output")]
+
+    def run(self, output_names, feeds):
+        self.output_names = output_names
+        self.feeds = feeds
+        source = feeds["input"]
+        return [np.repeat(np.repeat(source, 4, axis=2), 4, axis=3)]
+
+
+class UpscaleOnnxTest(unittest.TestCase):
+    def test_wider_context_preserves_pixels_across_odd_and_small_images(self):
+        for width, height in [(1, 1), (7, 5), (321, 163)]:
+            pixels = np.random.default_rng(7).integers(0, 256, (height, width, 3), dtype=np.uint8)
+            result = onnx_upscale.infer(FakeSession(), Image.fromarray(pixels), tile_border=48)
+            expected = np.repeat(np.repeat(pixels, 4, axis=0), 4, axis=1)
+            np.testing.assert_array_equal(np.asarray(result), expected)
+
+
+    def test_preprocess_matches_dynamic_rgb_layout(self):
+        image = Image.new("RGB", (7, 5), (64, 128, 192))
+
+        result = onnx_upscale.preprocess(image)
+
+        self.assertEqual(result.shape, (1, 3, 5, 7))
+        self.assertEqual(result.dtype, np.float32)
+        self.assertTrue(result.flags.c_contiguous)
+        np.testing.assert_allclose(
+            result[0, :, 0, 0],
+            np.array((64, 128, 192), dtype=np.float32) / 255.0,
+        )
+
+    def test_infer_returns_direct_four_x_rgb_prediction(self):
+        session = FakeSession()
+        image = Image.new("RGB", (7, 5), (10, 20, 30))
+
+        result = onnx_upscale.infer(session, image)
+
+        self.assertEqual(result.mode, "RGB")
+        self.assertEqual(result.size, (28, 20))
+        self.assertEqual(session.output_names, ["output"])
+        self.assertEqual(session.feeds["input"].shape, (1, 3, 256, 256))
+        self.assertEqual(result.getpixel((0, 0)), (10, 20, 30))
+
+    def test_infer_returns_raw_rgb_for_rgba_input(self):
+        session = FakeSession()
+        pixels = np.zeros((5, 7, 4), dtype=np.uint8)
+        pixels[..., :3] = (10, 20, 30)
+        pixels[..., 3] = np.arange(7, dtype=np.uint8) * 40
+        image = Image.fromarray(pixels, mode="RGBA")
+
+        result = onnx_upscale.infer(session, image)
+
+        self.assertEqual(result.mode, "RGB")
+        self.assertEqual(result.size, (28, 20))
+        self.assertEqual(result.getpixel((0, 0)), (10, 20, 30))
+
+    def test_tiles_use_reflected_context_at_outer_image_edges(self):
+        class RecordingSession(FakeSession):
+            def run(self, output_names, feeds):
+                self.input = feeds["input"].copy()
+                return super().run(output_names, feeds)
+
+        pixels = np.zeros((5, 7, 3), dtype=np.uint8)
+        pixels[..., 0] = np.arange(7, dtype=np.uint8) * 20
+        session = RecordingSession()
+
+        onnx_upscale.infer(
+            session,
+            Image.fromarray(pixels, mode="RGB"),
+        )
+
+        red = session.input[0, 0]
+        self.assertAlmostEqual(red[16, 22], 120 / 255.0)
+        self.assertAlmostEqual(red[16, 23], 100 / 255.0)
+
+
+    def test_all_models_split_large_inputs_into_fixed_tiles(self):
+        class CountingSession(FakeSession):
+            def __init__(self):
+                self.calls = 0
+
+            def run(self, output_names, feeds):
+                self.calls += 1
+                return super().run(output_names, feeds)
+
+        session = CountingSession()
+        result = onnx_upscale.infer(
+            session,
+            Image.new("RGB", (449, 225), (1, 2, 3)),
+        )
+
+        self.assertEqual(result.size, (1796, 900))
+        self.assertEqual(session.calls, 6)
+        self.assertEqual(session.feeds["input"].shape, (1, 3, 256, 256))
+
+    def test_only_final_tile_releases_memory(self):
+        releases = []
+        session = FakeSession()
+
+        def run(model, output_names, feeds, *, release_memory):
+            releases.append(release_memory)
+            return model.run(output_names, feeds)
+
+        with patch.object(onnx_upscale, "run_session", side_effect=run):
+            result = onnx_upscale.infer(
+                session,
+                Image.new("RGB", (449, 225), (1, 2, 3)),
+            )
+
+        self.assertEqual(result.size, (1796, 900))
+        self.assertEqual(releases, [False, False, False, False, False, True])
+
+    def test_non_final_image_does_not_release_its_final_tile(self):
+        releases = []
+        session = FakeSession()
+
+        def run(model, output_names, feeds, *, release_memory):
+            releases.append(release_memory)
+            return model.run(output_names, feeds)
+
+        with patch.object(onnx_upscale, "run_session", side_effect=run):
+            onnx_upscale.infer(
+                session,
+                Image.new("RGB", (449, 225), (1, 2, 3)),
+                release_memory=False,
+            )
+
+        self.assertEqual(releases, [False] * 6)
+
+    def test_provider_unicode_error_is_presented_as_resource_error(self):
+        class InvalidProviderSession(FakeSession):
+            def run(self, _output_names, _feeds):
+                raise UnicodeDecodeError("utf-8", b"\xc4", 0, 1, "invalid")
+
+        with self.assertRaisesRegex(
+            onnx_upscale.UpscaleResourceError,
+            "provider failed",
+        ):
+            onnx_upscale.infer(
+                InvalidProviderSession(),
+                Image.new("RGB", (7, 5)),
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()