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Add condlane #20

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merged 15 commits into from
Sep 11, 2021
Merged

Add condlane #20

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f397ff0
add condlane
Turoad Jun 8, 2021
8d6e022
update condlane
Turoad Jun 19, 2021
11a62a9
fix interface
Jun 19, 2021
8a963a3
fix
Jun 20, 2021
d3e23e8
minor fix
Turoad Jun 28, 2021
2c80bfe
update config & rename models
Turoad Jun 28, 2021
bd6a70f
add README.md for condlane
Turoad Jul 2, 2021
99f09eb
update datasets/registry
Turoad Jul 8, 2021
9faf0dc
remove some magic number
Turoad Jul 8, 2021
f16d2d3
Merge branch 'condlane' of https://github.com/Turoad/lanedet into con…
Turoad Jul 8, 2021
315ce63
add condlane resnet50
Turoad Jul 8, 2021
5891920
minor fix
Turoad Jul 8, 2021
3fa3b9b
update readme
Turoad Sep 7, 2021
2fa9fca
minor fix
Turoad Sep 10, 2021
28ef010
Merge branch 'main' into condlane
Turoad Sep 10, 2021
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17 changes: 17 additions & 0 deletions configs/condlane/README.md
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Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
# CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

## Introduction

```latex
@article{liu2021condlanenet,
title={CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution},
author={Liu, Lizhe and Chen, Xiaohao and Zhu, Siyu and Tan, Ping},
journal={arXiv preprint arXiv:2105.05003},
year={2021}
}
```

## Models
| Architecture| Backbone |Dataset | Metric | Config| Checkpoints |
|-------------|----------|--------|--------|-------|--------------|
| CondLane | ResNet101 | CULane | F1: 76.46| [config]() |[model](https://github.com/Turoad/lanedet/releases/download/1.0/condlane_r101_culane.pth.zip) |
5 changes: 2 additions & 3 deletions lanedet/datasets/registry.py
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Expand Up @@ -32,16 +32,15 @@ def build_dataloader(split_cfg, cfg, is_train=True):
shuffle = True
else:
shuffle = False
batch_size=cfg.batch_size

dataset = build_dataset(split_cfg, cfg)

init_fn = partial(
worker_init_fn, seed=cfg.seed)

samples_per_gpu = batch_size#cfg.batch_size // cfg.gpus
samples_per_gpu = cfg.batch_size // cfg.gpus
data_loader = torch.utils.data.DataLoader(
dataset, batch_size = batch_size, shuffle = shuffle,
dataset, batch_size = cfg.batch_size, shuffle = shuffle,
num_workers = cfg.workers, pin_memory = False, drop_last = False,
collate_fn=partial(collate, samples_per_gpu=samples_per_gpu),
worker_init_fn=init_fn)
Expand Down