Add tests for clipboard image functionality and mesh plane asset creation

- Implemented a comprehensive test suite for the clipboard image module, covering various functionalities including operator registration, context handling, and image processing.
- Created a new mesh plane asset with customizable parameters and integrated it into the geometry node system.
- Developed a validation script to ensure the correct behavior of the mesh plane asset, including input handling and output verification.

tests/test_server.py

@@ -220,6 +220,7 @@ class ServerTest(unittest.TestCase):
                 "download-model",
                 "download-required-models",
                 "analyze-balloon",
+                "analyze-image-lasso",
                 "remove-background",
                 "extract-frames",
                 "generate-depth",
@@ -400,6 +401,46 @@ class ServerTest(unittest.TestCase):
         self.assertEqual(tuple(result[0, 0]), (20, 40, 60, 64))
         self.assertEqual(tuple(result[3, 3]), (0, 0, 0, 0))
 
+    def test_image_lasso_canvas_clears_rgba_outside_the_selection(self):
+        import numpy as np
+        from PIL import Image
+
+        image_lasso = sys.modules["server.jobs.image_lasso"]
+        source_path = self.storage_root / "source.png"
+        pixels = np.full((2, 2, 4), (20, 40, 60, 255), dtype=np.uint8)
+        Image.fromarray(pixels, mode="RGBA").save(source_path)
+
+        canvas, _selection, bounds = image_lasso.create_lasso_canvas(
+            source_path,
+            ((-1, -1), (2, -1), (-1, 2)),
+        )
+        result = np.asarray(canvas)
+
+        self.assertEqual(bounds, (-1, -1, 2, 2))
+        self.assertEqual(result.shape, (3, 3, 4))
+        self.assertEqual(tuple(result[2, 2]), (0, 0, 0, 0))
+        self.assertEqual(tuple(result[1, 1]), (20, 40, 60, 255))
+
+    def test_image_lasso_crops_to_alpha_with_pixel_padding(self):
+        import numpy as np
+        from PIL import Image
+
+        image_lasso = sys.modules["server.jobs.image_lasso"]
+        pixels = np.zeros((4, 5, 4), dtype=np.uint8)
+        pixels[1:3, 2:4] = (20, 40, 60, 255)
+        result, bounds = image_lasso.crop_to_alpha(
+            Image.fromarray(pixels, mode="RGBA"),
+            (10, 20, 15, 24),
+            padding=1,
+        )
+        result = np.asarray(result)
+
+        self.assertEqual(bounds, (11, 20, 15, 24))
+        self.assertEqual(result.shape, (4, 4, 4))
+        self.assertTrue(np.all(result[[0, -1], :, 3] == 0))
+        self.assertTrue(np.all(result[:, [0, -1], 3] == 0))
+        self.assertTrue(np.all(result[1:3, 1:3, 3] == 255))
+
     def test_balloon_job_sends_the_masked_crop_to_ben2(self):
         import numpy as np
         from PIL import Image