Method _run_inference

benchmark/methods/lingbot_map.py:149–188

Run LingbotMap inference and return raw predictions dict.

(self, images)

        return images.to(self.device)

    def _run_inference(self, images):
        """Run LingbotMap inference and return raw predictions dict."""
        if self.use_amp:
            dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] >= 8 else torch.float16
        else:
            dtype = torch.float32

        print(f"  → Running {self.mode} inference (dtype: {dtype})")

        num_frames = images.shape[0]
        with torch.no_grad(), torch.amp.autocast("cuda", dtype=dtype):
            if self.mode == 'streaming':
                keyframe_interval = _resolve_keyframe_interval(
                    self.keyframe_interval, num_frames, self.auto_keyframe_threshold
                )
                if keyframe_interval != self.keyframe_interval:
                    print(
                        f"  → Auto-selected keyframe_interval={keyframe_interval} "
                        f"(num_frames={num_frames}, raw={self.keyframe_interval!r}, "
                        f"threshold={self.auto_keyframe_threshold})"
                    )
                predictions = self.model.inference_streaming(
                    images,
                    num_scale_frames=self.num_scale_frames,
                    keyframe_interval=keyframe_interval,
                    output_device=torch.device("cpu"),
                )
            else:
                predictions = self.model.inference_windowed(
                    images,
                    window_size=self.window_size,
                    overlap_size=self.overlap_size,
                    num_scale_frames=self.num_scale_frames,
                    keyframe_interval=self.keyframe_interval,
                    flow_threshold=self.flow_threshold,
                    max_non_keyframe_gap=self.max_non_keyframe_gap,
                    output_device=torch.device("cpu"),
                )

        return predictions

    def _process_outputs(self, predictions, image_shape):
        """Convert model predictions to benchmark output format.