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license: other
tags:
- heal
- horizon
- bev
- lane-detection
---
# MapTR+HENet (BevFormer)
MapTR uses HENet as the camera backbone to extract multi-view features, transforms them to BEV features via BevFormer's single-frame ViewTransformer and BEV Encoder, then feeds BEV features to the MapTR decoder with fixed-point polyline queries (`fixed_ptsnum_per_pred_line=20`) to predict vectorized map elements (divider/ped_crossing/boundary). This task has `use_lidar_gt=False`; map GT is generated online.
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## Deployment Metrics
### Model Parameters
| Model | Model Input | Backbone | Neck | Model Output |
|---|---|---|---|---|
| MapTR | 6-camera multi-view images `(B,6,3,480,800)` | HENet-tiny | FPN | vectorized map `(B,L,P,2)` |
### Accuracy Metrics
| March | Metric | float | calibration | qat | hbm |
| --- | --- | --- | --- | --- | --- |
| J6M | chamfer mAP (MAP) | 0.6626 | 0.6588 | — | 0.6315 |
> Data tested with `march = March.NASH_M` (J6M); this task has no QAT stage (`—` in the qat column).
>
> HEAL versions: heal 0.0.2 / hbdk4-compiler 4.11.11 / horizon_plugin_pytorch 3.3.10.
### Performance Metrics
> **Performance test methodology**: FPS is measured with 8 threads on a single core; Latency is measured with single core, single thread; Memory is peak DDR usage.
| March | latency (ms) | fps | Memory Usage |
|---|---|---|---|
| J6M | 9.30 | 111.22 | 88.40 |
| J6P | 6.16 | 663.68 | 83.30 |
| J6B | 33.28 | 30.85 | 80.00 |
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## Model Overview
### Core Design
MapTR uses HENet as the camera backbone to extract multi-view features, transforms them to BEV features via BevFormer's single-frame ViewTransformer and BEV Encoder, then feeds BEV features to the MapTR decoder with fixed-point polyline queries (`fixed_ptsnum_per_pred_line=20`) to predict vectorized map elements (divider/ped_crossing/boundary). This task has `use_lidar_gt=False`; map GT is generated online.
- **Task type**: Online Vectorized Map Construction.
- **backbone**: HENet-tiny (pretrained), extracts multi-view camera features.
- **neck**: FPN.
- **view transformation**: `SingleFrameBevFormerViewTransformer` + `SingleFrameBEVFormerEncoder` (`queue_length=1`/`test_queue_length=1`).
- **map elements**: `map_classes=[divider, ped_crossing, boundary]`, `fixed_ptsnum_per_gt_line=20`.
- **BEV range**: `use_lidar_gt=False` else branch, `point_cloud_range=[-30.0,-15.0,-10.0,30.0,15.0,10.0]`, `bev_h_=50`, `bev_w_=100` (bev 50×100).
- **Model input**: 6-camera single-frame images `(B,6,3,480,800)` .
- **Model output**: 3 classes of vectorized map elements (divider/ped_crossing/boundary), 20 points per line.
### Official Repo and Paper
Official repo: https://github.com/hustvl/MapTR
Paper: https://arxiv.org/abs/2208.14437
Note: The camera backbone HENet is developed in HEAL; the official repo uses a different backbone.
### Reference
For more J6 chip deployment details, see https://developer.horizon.auto/blog/14100
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