Add README.md

README.md

@@ -0,0 +1,70 @@
+---
+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.
+
+---
+
+## 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 |
+
+---
+
+## 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/10142