32 change image codex live preview

src/ffsplat/coding/scene_encoder.py

@@ -182,11 +182,11 @@ def to_yaml_file(self, yaml_path: Path) -> None:
 
 
 @lru_cache
-def process_operation(op: Operation, verbose: bool, decoding_ops: str) -> tuple[dict[str, Field], list[dict[str, Any]]]:
+def process_operation(op: Operation, verbose: bool) -> tuple[dict[str, Field], list[dict[str, Any]]]:
     """Process the operation and return the new fields and decoding updates."""
     if verbose:
         print(f"Encoding {op}...")
-    return op.apply(verbose=verbose, decoding_params_hashable=decoding_ops)
+    return op.apply(verbose=verbose)
 
 
 @dataclass
@@ -205,9 +205,12 @@ def _encode_fields(self, verbose: bool) -> None:
             input_fields_params = op_params["input_fields"]
             for transform_param in op_params["transforms"]:
                 op = Operation.from_json(input_fields_params, transform_param, self.fields, self.output_path)
-                new_fields, decoding_updates = process_operation(
-                    op, verbose=verbose, decoding_ops=self.decoding_params.to_yaml()
-                )
+                if op.transform_type != "write_file":
+                    new_fields, decoding_updates = process_operation(op, verbose=verbose)
+                else:
+                    new_fields, decoding_updates = op.apply(
+                        verbose=verbose, decoding_params_hashable=self.decoding_params.to_yaml()
+                    )
                 #  if the coding_updates are not a copy the cache will be wrong
                 for decoding_update in copy.deepcopy(decoding_updates):
                     # if the last decoding update has the same input fields we can combine the transforms into one list

src/ffsplat/conf/format/SOG-PlayCanvas.yaml

@@ -37,7 +37,7 @@ ops:
 
   - input_fields: [quaternions]
     transforms:
-      - reparametize:
+      - reparametrize:
           method: unit_sphere
           dim: -1
 
@@ -122,7 +122,7 @@ ops:
 
   - input_fields: [quats]
     transforms:
-      - reparametize:
+      - reparametrize:
           method: pack_quaternions
           to_fields_with_prefix: quats_packed_
           dim: -1

src/ffsplat/models/operations.py

@@ -69,5 +69,7 @@ def to_json(self) -> dict[str, Any]:
             "params": self.params,
         }
 
-    def apply(self, verbose: bool, decoding_params_hashable: str) -> tuple[dict[str, "Field"], list[dict[str, Any]]]:
+    def apply(
+        self, verbose: bool, decoding_params_hashable: str | None = None
+    ) -> tuple[dict[str, "Field"], list[dict[str, Any]]]:
         return apply_transform(self, verbose=verbose, decoding_params_hashable=decoding_params_hashable)

src/ffsplat/models/transformations.py

@@ -432,7 +432,7 @@ def apply(
                     "input_fields": [f"{to_fields_with_prefix}indices", f"{to_fields_with_prefix}values"],
                     "transforms": [
                         {
-                            "reparametize": {
+                            "reparametrize": {
                                 "method": "unpack_quaternions",
                                 "from_fields_with_prefix": to_fields_with_prefix,
                                 "dim": -1,
@@ -1114,7 +1114,7 @@ def apply(
                 field_names = list(parentOp.input_fields.keys())
                 meta: dict[str, Any] = {
                     "packer": "ffsplat",
-                    "version": 1,
+                    "version": 1.0,
                 }
                 # Readfile no input_fields
                 for field_name in field_names:
@@ -1457,7 +1457,7 @@ def get_dynamic_params(params: dict[str, Any]) -> list[dict[str, Any]]:
     "flatten": Flatten,
     "reshape": Reshape,
     "remapping": Remapping,
-    "reparametize": Reparametrize,
+    "reparametrize": Reparametrize,
     "to_field": ToField,
     "permute": Permute,
     "to_dtype": ToDType,
@@ -1473,13 +1473,15 @@ def get_dynamic_params(params: dict[str, Any]) -> list[dict[str, Any]]:
 
 
 def apply_transform(
-    parentOp: "Operation", verbose: bool, decoding_params_hashable: str
+    parentOp: "Operation", verbose: bool, decoding_params_hashable: str | None
 ) -> tuple[dict[str, "Field"], list[dict[str, Any]]]:
     transformation = transformation_map.get(parentOp.transform_type)
     if transformation is None:
         raise ValueError(f"Unknown transformation: {parentOp.transform_type}")
     elif transformation is WriteFile:
-        decoding_ops: list[dict[str, Any]] = yaml.load(decoding_params_hashable, Loader=yaml.SafeLoader)["ops"]
+        decoding_ops: list[dict[str, Any]] = []
+        if decoding_params_hashable is not None:
+            decoding_ops = yaml.load(decoding_params_hashable, Loader=yaml.SafeLoader)["ops"]
         return transformation.apply(
             parentOp.params[parentOp.transform_type], parentOp, verbose=verbose, decoding_ops=decoding_ops
         )