下位机&yolov11输出

root@tte:/mnt/sd-boot/lyp/rmfsd_Mul_cpp# ./vx_app_tidl_mul_rmfsd_copy_exe.out --cfg ./config/app_oc_piliang_dy.cfg

APP: Init ... !!!

MEM: Init ... !!!

MEM: Initialized DMA HEAP (fd=4) !!!

MEM: Init ... Done !!!

IPC: Init ... !!!

_rpmsg_char_find_ctrldev: could not find the matching rpmsg_ctrl device for virtio3.rpmsg_chrdev.-1.13

IPC: ERROR: Unable to create TX channels for CPU [mcu2_1] !!!

IPC: Init ... Done !!!

REMOTE_SERVICE: Init ... !!!

_rpmsg_char_find_ctrldev: could not find the matching rpmsg_ctrl device for virtio3.rpmsg_chrdev.-1.21

REMOTE_SERVICE: Init ... Done !!!

APP: Init ... Done !!!

hello: ./vx_app_tidl_mul_rmfsd_copy_exe.out

app_tidl: Init ...

app_tidl: Reading config file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin ...

app_tidl: Reading config file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin ... Done. 37256 bytes

app_tidl: Tensors, input = 1, output = 5

app_tidl: Reading network file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin ...

app_tidl: Reading network file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin ... Done. 9807044 bytes

app_tidl: Init ... Done.

app_tidl: Creating graph ...

app_tidl: Creating graph ... Done.

app_tidl: Verifying graph ...

app_tidl: Verifying graph ... Done.

network file: /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin

config file: /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin

Iteration 0 of 1 ...

exit_begin

root@tte:/mnt/sd-boot/lyp/rmfsd_Mul_cpp# bash mount.sh

root@10.2.2.81's password:

root@10.2.2.81's password:

root@tte:/mnt/sd-boot/lyp/rmfsd_Mul_cpp# ./vx_app_tidl_mul_rmfsd_copy_exe.out --cfg ./config/app_oc_piliang_dy.cfg

APP: Init ... !!!

MEM: Init ... !!!

MEM: Initialized DMA HEAP (fd=4) !!!

MEM: Init ... Done !!!

IPC: Init ... !!!

_rpmsg_char_find_ctrldev: could not find the matching rpmsg_ctrl device for virtio3.rpmsg_chrdev.-1.13

IPC: ERROR: Unable to create TX channels for CPU [mcu2_1] !!!

IPC: Init ... Done !!!

REMOTE_SERVICE: Init ... !!!

_rpmsg_char_find_ctrldev: could not find the matching rpmsg_ctrl device for virtio3.rpmsg_chrdev.-1.21

REMOTE_SERVICE: Init ... Done !!!

APP: Init ... Done !!!

hello: ./vx_app_tidl_mul_rmfsd_copy_exe.out

app_tidl: Init ...

app_tidl: Reading config file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin ...

app_tidl: Reading config file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin ... Done. 37256 bytes

app_tidl: Tensors, input = 1, output = 5

app_tidl: Reading network file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin ...

app_tidl: Reading network file /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin ... Done. 9807044 bytes

app_tidl: Init ... Done.

app_tidl: Creating graph ...

app_tidl: Creating graph ... Done.

app_tidl: Verifying graph ...

app_tidl: Verifying graph ... Done.

network file: /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_net_MulTask_fsd_rmfsd_608_736_last_115_V1_4M.bin

config file: /mnt/sd-boot/lyp/rmfsd_Mul_cpp/model/out_dynamic_608_736/tidl_io_MulTask_fsd_rmfsd_608_736_last_115_V1_4M_1.bin

Iteration 0 of 1 ...

Classifying input 1.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/1.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55511 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 487 us

检测到0车位

save to /mnt/cyData/lyp2/out_608_736//img/1_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/1_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/1_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/1_imask4.bmp!!!

完成图像张数: 1

Classifying input 1.bmp ...Done!

cur_time:==744589

Classifying input 2.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/2.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55323 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 499 us

检测到0车位

save to /mnt/cyData/lyp2/out_608_736//img/2_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/2_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/2_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/2_imask4.bmp!!!

完成图像张数: 2

Classifying input 2.bmp ...Done!

cur_time:==728003

Classifying input 3.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/3.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55188 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 573 us

检测到12车位

save to /mnt/cyData/lyp2/out_608_736//img/3_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/3_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/3_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/3_imask4.bmp!!!

完成图像张数: 3

Classifying input 3.bmp ...Done!

cur_time:==735126

Classifying input 4.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/4.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55252 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 658 us

检测到7车位

save to /mnt/cyData/lyp2/out_608_736//img/4_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/4_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/4_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/4_imask4.bmp!!!

完成图像张数: 4

Classifying input 4.bmp ...Done!

cur_time:==729634

Classifying input 5.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/5.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55202 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 327 us

检测到0车位

save to /mnt/cyData/lyp2/out_608_736//img/5_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/5_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/5_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/5_imask4.bmp!!!

完成图像张数: 5

Classifying input 5.bmp ...Done!

cur_time:==737908

Classifying input 6.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/6.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55218 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 184 us

检测到6车位

save to /mnt/cyData/lyp2/out_608_736//img/6_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/6_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/6_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/6_imask4.bmp!!!

完成图像张数: 6

Classifying input 6.bmp ...Done!

cur_time:==728608

Classifying input 7.bmp ...

app_tidl: Reading input file /mnt/cyData/lyp/image/7.bmp ... input_sizes[0] = 608, dim = 608 padL = 0 padR = 0

input_sizes[1] = 736, dim = 736 padT = 0 padB = 0

input_sizes[2] = 3, dim = 3

app_tidl: Reading bmp file ...

app_tidl: Reading bmp file ... Done.

app_tidl: Image Pre processing for image of size 480 x 544 (pitch = 1440 bytes)...

app_tidl: Deinterleaving data ...

app_tidl: Resizing image ...

app_tidl: Rearranging data ...

app_tidl: Image Pre processing ... Done.

Done!

app_tidl: Running Graph ... Done!

20260122==============!

time of rmfsd: 55259 us

写死来确保解码使用的输入尺寸有效

obj->yolov5params.inWidth[0] = obj->ioBufDesc.inWidth[0];

端到端车位解码耗时

端到端车位解码耗时: 702 us

检测到17车位

save to /mnt/cyData/lyp2/out_608_736//img/7_gmask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/7_imask0.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/7_gmask4.bmp!!!

save to /mnt/cyData/lyp2/out_608_736//img/7_imask4.bmp!!!

完成图像张数: 7

Classifying input 7.bmp ...Done!

cur_time:==733733

Classifying input 8.bmp ...

(mmd3.0) root@ai:/ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11# python /ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/train2.py

YOLOv5_mtl 🚀 2026-1-27 torch 1.10.1+cu113 CUDA:0 (NVIDIA A100-PCIE-80GB, 80994.8125MB)

Namespace(adam=False, artifact_alias='latest', backbone_weights='/ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/yolo11s.pt', batch_size=64, bbox_interval=-1, bucket='', cache_images=False, calc_macs=False, cfg='models/yolov11_custom_seg_big.yaml', data='data/custom.yaml', device='0', entity=None, epochs=150, evolve=False, exist_ok=False, extra_weights='', global_rank=-1, hyp='data/hyp.scratch.yaml', image_weights=True, img_size=[544, 544], label_smoothing=0.1, linear_lr=False, local_rank=-1, multi_scale=False, name='exp_lyp', noautoanchor=False, nosave=False, notest=False, prefer_ckpt_cfg=False, project='runs/train', quad=False, rect=False, resume='', save_dir='runs/train/exp_lyp5', save_period=-1, single_cls=False, strict_load=True, sync_bn=False, total_batch_size=64, upload_dataset=False, weights='/ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/runs/train/exp54/weights/last_99.pt', workers=8, world_size=1)

tensorboard: Start with 'tensorboard --logdir runs/train', view at http://localhost:6006/

hyperparameters: lr0=0.005, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, landmark=0.05, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.4, shear=0, perspective=0, flipud=0.0, fliplr=0.0, mosaic=0.0, mixup=0.243

wandb: Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)

from n params module arguments

0 -1 1 928 models.common.Conv [3, 32, 3, 2]

1 -1 1 18560 models.common.Conv [32, 64, 3, 2]

2 -1 1 26080 ultralytics.nn.modules.block.C3k2 [64, 128, 1, False, 0.25]

3 -1 1 147712 models.common.Conv [128, 128, 3, 2]

4 -1 1 103360 ultralytics.nn.modules.block.C3k2 [128, 256, 1, False, 0.25]

5 -1 1 590336 models.common.Conv [256, 256, 3, 2]

6 -1 1 346112 ultralytics.nn.modules.block.C3k2 [256, 256, 1, True]

7 -1 1 1180672 models.common.Conv [256, 512, 3, 2]

8 -1 1 1380352 ultralytics.nn.modules.block.C3k2 [512, 512, 1, True]

9 -1 1 656896 ultralytics.nn.modules.block.SPPF [512, 512, 5]

10 -1 1 990976 ultralytics.nn.modules.block.C2PSA [512, 512, 1]

11 -1 1 131584 models.common.Conv [512, 256, 1, 1]

12 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']

13 [-1, 6] 1 0 models.common.Concat [1]

14 -1 1 361984 models.common.C3 [512, 256, 1, False]

15 -1 1 33024 models.common.Conv [256, 128, 1, 1]

16 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']

17 [-1, 4] 1 0 models.common.Concat [1]

18 -1 1 493568 models.common.C3 [384, 256, 2, False]

19 -1 1 295168 models.common.Conv [256, 128, 3, 2]

20 [-1, 15] 1 0 models.common.Concat [1]

21 -1 1 460800 models.common.C3 [256, 256, 2, False]

22 -1 1 295168 models.common.Conv [256, 128, 3, 2]

23 [-1, 11] 1 0 models.common.Concat [1]

24 -1 1 493568 models.common.C3 [384, 256, 2, False]

25 [17, 13, 9] 1 2294800 models.yolo.SegMaskPSP [2, 1, 256, False, [384, 512, 512]]

26 [18, 21, 24] 1 50886 models.yolo.Detect [3, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [256, 256, 256]]

/ai/zhdata/lyp/conda/anaconda3/envs/mmd3.0/lib/python3.8/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2157.)

return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]

Model Summary: 571 layers, 10352534 parameters, 10352534 gradients, 43.1 GFLOPS

Transferred 65/744 items from /ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/runs/train/exp54/weights/last_99.pt

Transferred 240/744 items from /ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/yolo11s.pt

data/custom.yaml

/ai/TopViewMul/txt/1219/train_img_list_v16_new_128.txt

/ai/TopViewMul/txt/1219/test_img_list_v16_new_128.txt

'/ai/TopViewMul/txt/1219/train_cpp_v32_20251219_gt_new_128.txt'

'/ai/TopViewMul/txt/1219/val_cpp_v32_20251219_gt_new_128.txt'

/ai/TopViewMul/txt/1219/train_img_list_v16_new_128.txt

'/ai/TopViewMul/txt/1219/train_v39_20251219_gt_new_128.txt'

'/ai/TopViewMul/txt/1219/val_v39_20251219_gt_new_128.txt'

Scaled weight_decay = 0.0005

Optimizer groups: 127 .bias, 127 conv.weight, 122 other

Traceback (most recent call last):

File "/ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/train2.py", line 803, in <module>

train(hyp, opt, device, tb_writer)

File "/ai/zhdata/lyp/multiyolov5_point_v2_tda4cpp_yolov11/train2.py", line 239, in train

optimizer.load_state_dict(ckpt['optimizer'])

File "/ai/zhdata/lyp/conda/anaconda3/envs/mmd3.0/lib/python3.8/site-packages/torch/optim/optimizer.py", line 146, in load_state_dict

raise ValueError("loaded state dict contains a parameter group "

ValueError: loaded state dict contains a parameter group that doesn't match the size of optimizer's group

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