cb1bf9f372
* segmenter: add model * update * readme: update * config: update * segmenter: update readme * segmenter: update * segmenter: update * segmenter: update * configs: set checkpoint path to pretrain folder * segmenter: modify vit-s/lin, remove data config * rreadme: update * configs: transfer from _base_ to segmenter * configs: add 8x1 suffix * configs: remove redundant lines * configs: cleanup * first attempt * swipe CI error * Update mmseg/models/decode_heads/__init__.py Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> * segmenter_linear: use fcn backbone * segmenter_mask: update * models: add segmenter vit * decoders: yapf+remove unused imports * apply precommit * segmenter/linear_head: fix * segmenter/linear_header: fix * segmenter: fix mask transformer * fix error * segmenter/mask_head: use trunc_normal init * refactor segmenter head * Fetch upstream (#1) * [Feature] Change options to cfg-option (#1129) * [Feature] Change option to cfg-option * add expire date and fix the docs * modify docstring * [Fix] Add <!-- [ABSTRACT] --> in metafile #1127 * [Fix] Fix correct num_classes of HRNet in LoveDA dataset #1136 * Bump to v0.20.1 (#1138) * bump version 0.20.1 * bump version 0.20.1 * [Fix] revise --option to --options #1140 Co-authored-by: Rockey <41846794+RockeyCoss@users.noreply.github.com> Co-authored-by: MengzhangLI <mcmong@pku.edu.cn> * decode_head: switch from linear to fcn * fix init list formatting * configs: remove variants, keep only vit-s on ade * align inference metric of vit-s-mask * configs: add vit t/b/l * Update mmseg/models/decode_heads/segmenter_mask_head.py Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> * Update mmseg/models/decode_heads/segmenter_mask_head.py Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> * Update mmseg/models/decode_heads/segmenter_mask_head.py Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> * Update mmseg/models/decode_heads/segmenter_mask_head.py Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> * Update mmseg/models/decode_heads/segmenter_mask_head.py Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com> * model_converters: use torch instead of einops * setup: remove einops * segmenter_mask: fix missing imports * add necessary imported init funtion * segmenter/seg-l: set resolution to 640 * segmenter/seg-l: fix test size * fix vitjax2mmseg * add README and unittest * fix unittest * add docstring * refactor config and add pretrained link * fix typo * add paper name in readme * change segmenter config names * fix typo in readme * fix typos in readme * fix segmenter typo * fix segmenter typo * delete redundant comma in config files * delete redundant comma in config files * fix convert script * update lateset master version Co-authored-by: MengzhangLI <mcmong@pku.edu.cn> Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn> Co-authored-by: Rockey <41846794+RockeyCoss@users.noreply.github.com> Co-authored-by: Miao Zheng <76149310+MeowZheng@users.noreply.github.com>
25 lines
697 B
Python
25 lines
697 B
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import torch
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from mmseg.models.decode_heads import SegmenterMaskTransformerHead
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from .utils import _conv_has_norm, to_cuda
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def test_segmenter_mask_transformer_head():
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head = SegmenterMaskTransformerHead(
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in_channels=2,
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channels=2,
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num_classes=150,
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num_layers=2,
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num_heads=3,
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embed_dims=192,
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dropout_ratio=0.0)
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assert _conv_has_norm(head, sync_bn=True)
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head.init_weights()
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inputs = [torch.randn(1, 2, 32, 32)]
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if torch.cuda.is_available():
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head, inputs = to_cuda(head, inputs)
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outputs = head(inputs)
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assert outputs.shape == (1, head.num_classes, 32, 32)
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