  The inspection of power transmission line has achieved notable achievements
in the past few years, primarily due to the integration of deep learning
technology. However, current inspection approaches continue to encounter
difficulties in generalization and intelligence, which restricts their further
applicability. In this paper, we introduce Power-LLaVA, the first large
language and vision assistant designed to offer professional and reliable
inspection services for power transmission line by engaging in dialogues with
humans. Moreover, we also construct a large-scale and high-quality dataset
specialized for the inspection task. By employing a two-stage training strategy
on the constructed dataset, Power-LLaVA demonstrates exceptional performance at
a comparatively low training cost. Extensive experiments further prove the
great capabilities of Power-LLaVA within the realm of power transmission line
inspection. Code shall be released.
