Add image perspective editing and related tools

- Implemented the Image Perspective tool for editing image corners in Blender.
- Created a new operator `EditImagePerspective` to handle the perspective transformation.
- Added a preview feature for the perspective adjustment.
- Introduced the `ImagePolylineTool` for editing image masks with polylines.
- Developed backend support for Real-ESRGAN model inference, including ONNX integration.
- Added functionality for image masking and background removal.
- Created unit tests for the Real-ESRGAN ONNX model to ensure correct preprocessing and inference.

tests/test_realesrgan_onnx.py

@@ -0,0 +1,75 @@
+import sys
+import unittest
+from pathlib import Path
+from types import SimpleNamespace
+
+import numpy as np
+from PIL import Image
+
+
+SOURCE_DIR = (
+    Path(__file__).resolve().parents[1]
+    / "src"
+    / "anyimage"
+    / "server"
+    / "models"
+)
+sys.path.insert(0, str(SOURCE_DIR))
+
+import onnx_realesrgan
+
+
+class FakeSession:
+    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 RealesrganOnnxTest(unittest.TestCase):
+    def test_preprocess_matches_dynamic_rgb_layout(self):
+        image = Image.new("RGB", (7, 5), (64, 128, 192))
+
+        result = onnx_realesrgan.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_realesrgan.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, 5, 7))
+        self.assertEqual(result.getpixel((0, 0)), (10, 20, 30))
+
+    def test_infer_rejects_non_four_x_output(self):
+        class InvalidSession(FakeSession):
+            def run(self, _output_names, feeds):
+                return [feeds["input"]]
+
+        with self.assertRaisesRegex(RuntimeError, "unexpected output shape"):
+            onnx_realesrgan.infer(
+                InvalidSession(),
+                Image.new("RGB", (7, 5)),
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()