Method render

easyvolcap/runners/websocket_server.py:154–166

(self, batch: dotdict)

                log('Server image sum:', self.image.sum())

    def render(self, batch: dotdict):
        batch = self.dataset.get_viewer_batch(batch)
        batch = to_cuda(add_batch(add_iter(batch, self.iter, self.runner.total_iter)))

        # Forward pass
        self.runner.maybe_jit_model(batch)
        with torch.inference_mode(self.runner.test_using_inference_mode), torch.no_grad(), torch.cuda.amp.autocast(enabled=self.runner.test_use_amp, cache_enabled=self.runner.test_amp_cached):
            output = self.model(batch)

        image = self.runner.visualizer.generate_type(output, batch, self.visualization_type)[0][0]  # RGBA (should we use alpha?)
        image = image[..., :3]
        image = (image.clip(0, 1) * 255).type(torch.uint8).flip(0)  # transform
        return image  # H, W, 3