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#
# Licensed under the Apache License, Version 2.0 (the "License");
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# http://www.apache.org/licenses/LICENSE-2.0
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"""Visual (image) reward scoring functions for VeRL-Omni."""
[docs]
def default_compute_score_image(
data_source,
solution_image,
ground_truth,
extra_info=None,
**kwargs,
):
"""Compute the reward score for a visual (image) response.
Args:
data_source (str): Dataset identifier that determines the scoring method.
solution_image: The generated image, as a ``torch.Tensor`` in shape
``(C, H, W)`` or ``(N, C, H, W)``.
ground_truth (str): Ground-truth answer (may be unused for rule-based
rewards such as ``jpeg_compressibility``).
extra_info (dict, optional): Additional metadata passed by the reward
manager.
Returns:
float or dict: The computed score (or a dict with a ``"score"`` key).
Raises:
NotImplementedError: If no scorer is registered for *data_source*.
"""
if data_source == "jpeg_compressibility":
from . import jpeg_compressibility
res = jpeg_compressibility.compute_score(solution_image)
else:
raise NotImplementedError(f"Reward function is not implemented for {data_source=}")
if isinstance(res, dict):
return res
elif isinstance(res, int | float | bool):
return float(res)
else:
return float(res[0])
__all__ = ["default_compute_score_image"]