[Questionnaire] Which model do you want to support in mmdeploy?

[VVsssssk]

Which model do you want to support in mmdeploy? Comment here. You can like a comment to increase model priority.

	Model	Codebase	Backend	Number of likes	Released
1	Swin-Transformer	mmcls	tensorrt	2	v0.6.0
2	Second	mmdet3d	tensorrt	1
3	htc	mmdet	tensorrt	1
4	Segmenter	mmseg	tensorrt	1	v0.6.0
5	ConvNeXt	mmcls	tensorrt	1
6	MASTER	mmocr	tensorrt	1
7	ABINet	mmocr	tensorrt	1
8	BEVFormer	mmdet3d	tensorrt	1
9	Oriented R-CNN	mmrotate	tensorrt	1	v0.6.0
10	SAR	mmocr	tensorrt	1

Reference:

• MASTER: ocr识别模型master // Can MASTER from mmocr be deployed?  #623
• ABINet: ABINet deployment #689
• BEVFormer: Need to deploy MultiViewImage Model BEVFormer based on mmdet3d #688
• SAR: cannot find ResizeOCR implementation on specific platform cuda #630

[VVsssssk]

E.g:
Swin-Transformer mmcls tensorrt

[OrcunCanDeniz]

second mmdet3d tensorrt

[haofanwang]

htc mmdetection tensorrt

[haofanwang]

segmenter mmsegmentation tensorrt

[starhou]

swin-transformer mmdet tensorrt

[starhou]

I haven't tried the conversion yet and I just used your example fater-rcnn. Maybe now, need to try.

[RunningLeon]

segmenter mmsegmentation tensorrt

@haofanwang Have you tried segmenter with mmdeploy?

[haofanwang]

segmenter mmsegmentation tensorrt

@haofanwang Have you tried segmenter with mmdeploy?

@RunningLeon , Yes, but I receive error messages as below

TypeError: upsample_bicubic2d() received an invalid combination of arguments - got (Tensor, NoneType, bool, list), but expected one of:
 * (Tensor input, tuple of ints output_size, bool align_corners, tuple of floats scale_factors)
      didn't match because some of the arguments have invalid types: (Tensor, NoneType, bool, list)
 * (Tensor input, tuple of ints output_size, bool align_corners, float scales_h, float scales_w, *, Tensor out)

And my command is

python ./tools/deploy.py \
    ./configs/mmseg/segmentation_tensorrt-fp16_dynamic-512x1024-2048x2048.py \
    ./mmsegmentation/configs/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k.py \
    ./mmsegmentation/checkpoints/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750-7ef345be.pth \
    ./mmsegmentation/demo/demo.png \
    --work-dir work_dir\
    --device cuda\
    --dump-in

[RunningLeon]

512x512
@haofanwang
Try with static config with 512x512. You can change in config file.

[eliabruni]

maskformer mmdet tensorrt

[isjinghao]

swin-transformer mmdet onnx

[Siannodel]

Swin-Transformer mmcls tensorrt