TVPaint frame range definition

openpype/hosts/tvpaint/api/lib.py

@@ -77,8 +77,9 @@ def set_context_settings(asset_doc=None):
  handle_start = handles
  handle_end = handles
 
- frame_start -= int(handle_start)
- frame_end += int(handle_end)
+ # Always start from 0 Mark In and set only Mark Out
+ mark_in = 0
+ mark_out = mark_in + (frame_end - frame_start) + handle_start + handle_end
 
- execute_george("tv_markin {} set".format(frame_start - 1))
- execute_george("tv_markout {} set".format(frame_end - 1))
+ execute_george("tv_markin {} set".format(mark_in))
+ execute_george("tv_markout {} set".format(mark_out))

openpype/hosts/tvpaint/plugins/publish/collect_instance_frames.py

@@ -0,0 +1,37 @@
+import pyblish.api
+
+
+class CollectOutputFrameRange(pyblish.api.ContextPlugin):
+ """Collect frame start/end from context.
+
+ When instances are collected context does not contain `frameStart` and
+ `frameEnd` keys yet. They are collected in global plugin
+ `CollectAvalonEntities`.
+ """
+ label = "Collect output frame range"
+ order = pyblish.api.CollectorOrder
+ hosts = ["tvpaint"]
+
+ def process(self, context):
+ for instance in context:
+ frame_start = instance.data.get("frameStart")
+ frame_end = instance.data.get("frameEnd")
+ if frame_start is not None and frame_end is not None:
+ self.log.debug(
+ "Instance {} already has set frames {}-{}".format(
+ str(instance), frame_start, frame_end
+ )
+ )
+ return
+
+ frame_start = context.data.get("frameStart")
+ frame_end = context.data.get("frameEnd")
+
+ instance.data["frameStart"] = frame_start
+ instance.data["frameEnd"] = frame_end
+
+ self.log.info(
+ "Set frames {}-{} on instance {} ".format(
+ frame_start, frame_end, str(instance)
+ )
+ )

openpype/hosts/tvpaint/plugins/publish/collect_instances.py

@@ -86,9 +86,6 @@ def process(self, context):
 
  instance.data["publish"] = any_visible
 
- instance.data["frameStart"] = context.data["sceneMarkIn"] + 1
- instance.data["frameEnd"] = context.data["sceneMarkOut"] + 1
-
  self.log.debug("Created instance: {}\n{}".format(
  instance, json.dumps(instance.data, indent=4)
  ))