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# Copyright (c) 2024-present, BAAI. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ------------------------------------------------------------------------
"""Flex data pipelines."""
import multiprocessing
import cv2
import numpy.random as npr
from diffnext.data import flex_transforms
class Worker(multiprocessing.Process):
"""Base data worker."""
def __init__(self):
super().__init__(daemon=True)
self.seed = 1337
self.reader_queue = None
self.worker_queue = None
def run(self):
"""Run implementation."""
# Disable opencv threading and fix numpy random seed.
cv2.setNumThreads(1), npr.seed(self.seed)
while True: # Main loop.
self.worker_queue.put(self.get_outputs(self.reader_queue.get()))
class FeaturePipe(object):
"""Pipeline to transform data features."""
def __init__(self):
super().__init__()
self.parse_latents = flex_transforms.ParseLatents()
self.parse_annotations = flex_transforms.ParseAnnotations()
def get_outputs(self, inputs):
"""Return the outputs."""
latents = self.parse_latents(inputs)
label, caption = self.parse_annotations(inputs)
outputs = {"latents": [latents]}
outputs.setdefault("prompt", [label]) if label is not None else None
outputs.setdefault("prompt", [caption]) if caption is not None else None
outputs.setdefault("motion", [inputs["flow"]]) if "flow" in inputs else None
return outputs
class FeatureWorker(FeaturePipe, Worker):
"""Worker to transform data features."""
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