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add paddle3d and bevfusion model training #2749

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@warrentdrew warrentdrew commented Dec 31, 2024

add paddle3d and bevfusion model training. Original pr #2572

## 4. 数据准备和校验
### 4.1 数据准备

本教程采用 `nuScenes`数据集 作为示例数据集,请在[官网](https://www.nuscenes.org/nuscenes)进行下载,将数据集目录准备如下:
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这里最好把示例数据集上传到BOS上吧?

|—— v1.0-trainval
```

在`./paddlex/repo_manager/repos/Paddle3D`的目录下创建软链接 `data/nuscenes`,指向到上面的数据集目录:
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其实不太希望让用户在这个目录下创建内容,PaddleX对大多数用户来说,希望这个repos是无感的。这块看是否挪出去呢?

mkdir data
ln -s /path/to/nuscenes_dataset_root ./data
mv ./data/nuscenes_dataset_root ./data/nuscenes
```
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关于用户自己的数据如何制作和标注,需要补充文档说明下


BEVFusion模型训练需要加载camera分支模型预训练分支和lidar分支模型预训练权重:
```bash
wget https://paddle3d.bj.bcebos.com/models/bevfusion/camera/model.pdparams
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这一块需要内置到代码中,在config中配置,尽量不让用户手动执行这些操作

model: BEVFusion
mode: check_dataset
dataset_dir: "/paddle/dataset/paddlex/3d/nuscenes"
device: gpu:1,2,3,4 #0,1,2,3
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这里为什么是1,2,3,4呢?



Export:
weight_path: /paddle/model/paddlex/3d/fusion.pdparams
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这里应该写动态图权重的http链接


Evaluate:
batch_size: 1
weight_path: /paddle/model/paddlex/3d/fusion.pdparams
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这里写对应的output的动态图路径

@@ -0,0 +1,96 @@
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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2025



class BEVFusionTrainer(BaseTrainer):
"""Object Detection Model Trainer"""
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注释不对

@@ -0,0 +1,17 @@
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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2025,下同

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3 participants