能用到其他数据集吗 about persformer_3dlane HOT 7 CLOSED

如果是推理的话，只需要提供输入图像、相机内参和相机外参即可，对应代码中的变量就是input, gt_intrinsic和gt_extrinsic。

cam_height和pitch是从外参中计算得到，不需要额外设定。修改org_w和org_h即可。但目前代码只适配了OpenLane的数据格式，支持其训练和测试，还不能直接用于其他数据集（需要对应适配DataLoader）。对于单张图像的推理，一个简单的方式是按照OpenLane的数据集格式和路径格式准备对应的图片和标注（相机内参和相机外参从标注中读取）作为validation。

此外，由于nuscenes没有车道线标注，所以无法进行训练和定量的测试对比。需要注意的是，不经过finetune，直接使用OpenLane的预训练模型可能会由于数据集分布的差异导致效果不佳。

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@dyfcalid 感谢解答。
我试着测试了，用你们的数据集正常；用nuscene时发现生成的vis_ipm图像不对，怀疑是json里extrinsic参数有问题。那么extrinsic这个参数，是指camera to ego的Transformation Matrix吗，或者是world to camera?

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@dyfcalid 感谢解答。 我试着测试了，用你们的数据集正常；用nuscene时发现生成的vis_ipm图像不对，怀疑是json里extrinsic参数有问题。那么extrinsic这个参数，是指camera to ego的Transformation Matrix吗，或者是world to camera?

是的，camera to ego，相机坐标系到车辆坐标系

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你好，直接使用carema to ego测试结果是正确的吗？因为我尝试了一下ipm的可视化结果有问题，是因为openlane标注的waymo数据集的x，y和z轴和正常的偏向不同导致吗？

from persformer_3dlane.

from persformer_3dlane.

I used the original code of the Persformer model to predict front-view images in the NuScenes dataset, and I used the corresponding intrinsic and extrinsic parameters. However, when using Persformer for inference, the generated JSON results in result_3d show empty lane_lines. Besides changing the intrinsic and extrinsic parameters in the ground truth file, are there any other parameters that need to be adjusted during testing?

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Perhaps it's an issue with my input coordinate system? Because, upon investigating the problem, I found that during the compute_3d_lanes_all_category process, all the lane lines are being categorized as invalid lane lines (if np.argmax(category) == 0: continue). Consequently, the output 3D points are empty. I wanted to ask, during the testing of the NuScenes dataset with the camera parameters from the dataset,and chaning the ori_img_shape, have there been any modifications?"

from persformer_3dlane.