feat: example annotation oriented as annotation and mesh

Author: seankmartin

new_examples/convert_oriented_annotation-egczi1-mesh.py

@@ -0,0 +1,66 @@
+import json
+
+from cryoet_data_portal_neuroglancer.precompute.points import (
+    encode_annotation,
+)
+from cryoet_data_portal_neuroglancer.precompute.instance_mesh import (
+    encode_oriented_mesh,
+)
+from cryoet_data_portal_neuroglancer.state_generator import (
+    generate_oriented_point_layer,
+    combine_json_layers,
+    generate_segmentation_mask_layer,
+)
+from cryoet_data_portal_neuroglancer.io import load_glb_file, load_oriented_point_data
+from pathlib import Path
+from cryoet_data_portal_neuroglancer.precompute.glb_meshes import (
+    generate_standalone_sharded_multiresolution_mesh,
+)
+
+
+JSON_PATH = Path(
+    r"/media/starfish/LargeSSD/data/cryoET/data/Annotations-test-run/100-proton_transporting_atp_synthase_complex-1.0.json"
+)
+
+MESH_PATH = Path(
+    r"/media/starfish/LargeSSD/data/cryoET/data/meshes-oriented/atpase.glb"
+)
+
+OUTPUT_PATH = Path(r"/media/starfish/LargeSSD/data/cryoET/data/converted-01122021/")
+
+metadata, data = load_oriented_point_data(
+    JSON_PATH, JSON_PATH.with_name(JSON_PATH.stem + "_orientedpoint.ndjson")
+)
+
+encode_annotation(
+    data, metadata, OUTPUT_PATH, 0.784 * 1e-9, shard_by_id=(0, 10), is_oriented=True
+)
+mesh = load_glb_file(MESH_PATH)
+
+sub_result = encode_oriented_mesh(mesh, data, metadata, OUTPUT_PATH, 2)
+generate_standalone_sharded_multiresolution_mesh(
+    sub_result,
+    OUTPUT_PATH / "meshoutput",
+)
+
+SOURCE = "http://127.0.0.1:9000/converted-01122021/"
+
+output = generate_oriented_point_layer(
+    source=SOURCE,
+    name="Test Oriented Points",
+    color="#FFFFFF",
+    point_size_multiplier=0.5,
+    line_width=2.0,
+    is_visible=True,
+    is_instance_segmentation=False,
+    scale=0.784 * 1e-9,
+)
+
+output2 = generate_segmentation_mask_layer(
+    source="http://localhost:1337",
+    name="Test Mesh",
+    color="#FF0000",
+    scale=0.784 * 1e-9,
+)
+layer_json = combine_json_layers([output, output2], 0.784, units="nm")
+json.dump(layer_json, open("oriented_point_layer.json", "w"), indent=2)