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141 lines
4.4 KiB
Python
141 lines
4.4 KiB
Python
import os
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import tempfile
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import subprocess
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import pyblish.api
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from avalon import harmony
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import pype.lib
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import clique
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class ExtractRender(pyblish.api.InstancePlugin):
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"""Produce a flattened image file from instance.
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This plug-in only takes into account the nodes connected to the composite.
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"""
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label = "Extract Render"
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order = pyblish.api.ExtractorOrder
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hosts = ["harmony"]
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families = ["render"]
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def process(self, instance):
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# Collect scene data.
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application_path = instance.context.data.get("applicationPath")
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scene_path = instance.context.data.get("scenePath")
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frame_rate = instance.context.data.get("frameRate")
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frame_start = instance.context.data.get("frameStart")
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frame_end = instance.context.data.get("frameEnd")
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audio_path = instance.context.data.get("audioPath")
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if audio_path and os.path.exists(audio_path):
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self.log.info(f"Using audio from {audio_path}")
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instance.data["audio"] = [{"filename": audio_path}]
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instance.data["fps"] = frame_rate
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# Set output path to temp folder.
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path = tempfile.mkdtemp()
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sig = harmony.signature()
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func = """function %s(args)
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{
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node.setTextAttr(args[0], "DRAWING_NAME", 1, args[1]);
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}
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%s
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""" % (sig, sig)
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harmony.send(
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{
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"function": func,
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"args": [instance[0], path + "/" + instance.data["name"]]
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}
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)
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harmony.save_scene()
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# Execute rendering. Ignoring error cause Harmony returns error code
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# always.
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self.log.info(f"running [ {application_path} -batch {scene_path}")
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proc = subprocess.Popen(
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[application_path, "-batch", scene_path],
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stdout=subprocess.PIPE,
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stderr=subprocess.STDOUT,
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stdin=subprocess.PIPE
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)
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output, error = proc.communicate()
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self.log.info("Click on the line below to see more details.")
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self.log.info(output.decode("utf-8"))
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# Collect rendered files.
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self.log.debug(f"collecting from: {path}")
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files = os.listdir(path)
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assert files, (
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"No rendered files found, render failed."
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)
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self.log.debug(f"files there: {files}")
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collections, remainder = clique.assemble(files, minimum_items=1)
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assert not remainder, (
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"There should not be a remainder for {0}: {1}".format(
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instance[0], remainder
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)
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)
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self.log.debug(collections)
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if len(collections) > 1:
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for col in collections:
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if len(list(col)) > 1:
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collection = col
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else:
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collection = collections[0]
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# Generate thumbnail.
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thumbnail_path = os.path.join(path, "thumbnail.png")
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ffmpeg_path = pype.lib.get_ffmpeg_tool_path("ffmpeg")
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args = [
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ffmpeg_path, "-y",
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"-i", os.path.join(path, list(collections[0])[0]),
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"-vf", "scale=300:-1",
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"-vframes", "1",
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thumbnail_path
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]
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process = subprocess.Popen(
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args,
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stdout=subprocess.PIPE,
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stderr=subprocess.STDOUT,
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stdin=subprocess.PIPE
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)
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output = process.communicate()[0]
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if process.returncode != 0:
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raise ValueError(output.decode("utf-8"))
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self.log.debug(output.decode("utf-8"))
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# Generate representations.
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extension = collection.tail[1:]
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representation = {
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"name": extension,
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"ext": extension,
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"files": list(collection),
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"stagingDir": path,
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"tags": ["review"],
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"fps": frame_rate
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}
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thumbnail = {
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"name": "thumbnail",
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"ext": "png",
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"files": os.path.basename(thumbnail_path),
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"stagingDir": path,
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"tags": ["thumbnail"]
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}
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instance.data["representations"] = [representation, thumbnail]
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if audio_path and os.path.exists(audio_path):
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instance.data["audio"] = [{"filename": audio_path}]
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# Required for extract_review plugin (L222 onwards).
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instance.data["frameStart"] = frame_start
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instance.data["frameEnd"] = frame_end
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instance.data["fps"] = frame_rate
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self.log.info(f"Extracted {instance} to {path}")
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