ncnn2table crnn-opt.param crnn-opt.bin /tmp/imagelist.txt crnn.table mean=[128] norm=[0.007] s$ape=[32,128,1] pixel=GRAY thread=24 method=kl
mean = [128.000000]
norm = [0.007000]
shape = [32,128,1]
pixel = GRAY thread = 24
method = kl
--------------------------------------- count the absmax 0.00% [ 0 / 9459 ]
count the absmax 1.06% [ 100 / 9459 ]
count the absmax 2.11% [ 200 / 9459 ]
count the absmax 4.23% [ 400 / 9459 ]
count the absmax 3.17% [ 300 / 9459 ]
.....
count the absmax 81.40% [ 7700 / 9459 ]
count the absmax 82.46% [ 7800 / 9459 ]
count the absmax 83.52% [ 7900 / 9459 ]
count the absmax 84.58% [ 8000 / 9459 ]
count the absmax 85.63% [ 8100 / 9459 ]
count the absmax 86.69% [ 8200 / 9459 ]
count the absmax 87.75% [ 8300 / 9459 ]
count the absmax 88.80% [ 8400 / 9459 ]
count the absmax 89.86% [ 8500 / 9459 ]
count the absmax 90.92% [ 8600 / 9459 ]
count the absmax 91.98% [ 8700 / 9459 ]
count the absmax 93.03% [ 8800 / 9459 ]
count the absmax 95.15% [ 9000 / 9459 ]
count the absmax 96.20% [ 9100 / 9459 ]
count the absmax 94.09% [ 8900 / 9459 ]
count the absmax 97.26% [ 9200 / 9459 ]
count the absmax 98.32% [ 9300 / 9459 ]
count the absmax 99.38% [ 9400 / 9459 ]
build histogram 0.00% [ 0 / 9459 ]
Segmentation fault (core dumped)param:
mobilenet V3 + 1 LSTM
cat crnn-opt.param
7767517 155 174 Input images 0 1 images Convolution 326 1 1 images 327 0=8 1=3 3=2 4=1 5=1 6=72 HardSwish 333 1 1 327 333 0=1.666667e-01 Split splitncnn_0 1 2 333 333_splitncnn_0 333_splitncnn_1 Convolution 334 1 1 333_splitncnn_1 336 0=8 1=1 5=1 6=64 9=1 ConvolutionDepthWise 337 1 1 336 339 0=8 1=3 4=1 5=1 6=72 7=8 9=1 Convolution 340 1 1 339 341 0=8 1=1 5=1 6=64 BinaryOp 342 2 1 333_splitncnn_0 341 342 Convolution 343 1 1 342 345 0=32 1=1 5=1 6=256 9=1 ConvolutionDepthWise 346 1 1 345 348 0=32 1=3 13=2 4=1 5=1 6=288 7=32 9=1 Convolution 349 1 1 348 350 0=16 1=1 5=1 6=512 Split splitncnn_1 1 2 350 350_splitncnn_0 350_splitncnn_1 Convolution 351 1 1 350_splitncnn_1 353 0=40 1=1 5=1 6=640 9=1 ConvolutionDepthWise 354 1 1 353 356 0=40 1=3 4=1 5=1 6=360 7=40 9=1 Convolution 357 1 1 356 358 0=16 1=1 5=1 6=640 BinaryOp 359 2 1 350_splitncnn_0 358 359 Convolution 360 1 1 359 362 0=40 1=1 5=1 6=640 9=1 ConvolutionDepthWise 363 1 1 362 365 0=40 1=5 13=2 4=2 5=1 6=1000 7=40 9=1 Split splitncnn_2 1 2 365 365_splitncnn_0 365_splitncnn_1 Pooling 366 1 1 365_splitncnn_1 366 0=1 4=1 InnerProduct 367 1 1 366 368 0=10 1=1 2=400 9=1 InnerProduct 369 1 1 368 369 0=40 1=1 2=400 BinaryOp 371 1 1 369 371 0=2 1=1 2=1.200000e+00 HardSigmoid 376 1 1 371 376 0=1.666667e-01 BinaryOp 377 2 1 365_splitncnn_0 376 377 0=2 Convolution 378 1 1 377 379 0=24 1=1 5=1 6=960 Split splitncnn_3 1 2 379 379_splitncnn_0 379_splitncnn_1 Convolution 380 1 1 379_splitncnn_1 382 0=64 1=1 5=1 6=1536 9=1 ConvolutionDepthWise 383 1 1 382 385 0=64 1=5 4=2 5=1 6=1600 7=64 9=1 Split splitncnn_4 1 2 385 385_splitncnn_0 385_splitncnn_1 Pooling 386 1 1 385_splitncnn_1 386 0=1 4=1 InnerProduct 387 1 1 386 388 0=16 1=1 2=1024 9=1 InnerProduct 389 1 1 388 389 0=64 1=1 2=1024 BinaryOp 391 1 1 389 391 0=2 1=1 2=1.200000e+00 HardSigmoid 396 1 1 391 396 0=1.666667e-01 BinaryOp 397 2 1 385_splitncnn_0 396 397 0=2 Convolution 398 1 1 397 399 0=24 1=1 5=1 6=1536
BinaryOp 400 2 1 379_splitncnn_0 399 400
Split splitncnn_5 1 2 400 400_splitncnn_0 400_splitncnn_1
Convolution 401 1 1 400_splitncnn_1 403 0=64 1=1 5=1 6=1536 9=1
ConvolutionDepthWise 404 1 1 403 406 0=64 1=5 4=2 5=1 6=1600 7=64 9=1
Split splitncnn_6 1 2 406 406_splitncnn_0 406_splitncnn_1
Pooling 407 1 1 406_splitncnn_1 407 0=1 4=1
InnerProduct 408 1 1 407 409 0=16 1=1 2=1024 9=1
InnerProduct 410 1 1 409 410 0=64 1=1 2=1024
BinaryOp 412 1 1 410 412 0=2 1=1 2=1.200000e+00
HardSigmoid 417 1 1 412 417 0=1.666667e-01
BinaryOp 418 2 1 406_splitncnn_0 417 418 0=2
Convolution 419 1 1 418 420 0=24 1=1 5=1 6=1536
BinaryOp 421 2 1 400_splitncnn_0 420 421
Convolution 422 1 1 421 423 0=120 1=1 5=1 6=2880
HardSwish 429 1 1 423 429 0=1.666667e-01
ConvolutionDepthWise 430 1 1 429 431 0=120 1=3 4=1 5=1 6=1080 7=120
HardSwish 437 1 1 431 437 0=1.666667e-01
Convolution 438 1 1 437 439 0=40 1=1 5=1 6=4800
Split splitncnn_7 1 2 439 439_splitncnn_0 439_splitncnn_1
Convolution 440 1 1 439_splitncnn_1 441 0=104 1=1 5=1 6=4160
HardSwish 447 1 1 441 447 0=1.666667e-01
ConvolutionDepthWise 448 1 1 447 449 0=104 1=3 4=1 5=1 6=936 7=104
HardSwish 455 1 1 449 455 0=1.666667e-01
Convolution 456 1 1 455 457 0=40 1=1 5=1 6=4160
BinaryOp 458 2 1 439_splitncnn_0 457 458 Split splitncnn_8 1 2 458 458_splitncnn_0 458_splitncnn_1 Convolution 459 1 1 458_splitncnn_1 460 0=96 1=1 5=1 6=3840 HardSwish 466 1 1 460 466 0=1.666667e-01 ConvolutionDepthWise 467 1 1 466 468 0=96 1=3 4=1 5=1 6=864 7=96 HardSwish 474 1 1 468 474 0=1.666667e-01 Convolution 475 1 1 474 476 0=40 1=1 5=1 6=3840 BinaryOp 477 2 1 458_splitncnn_0 476 477 Split splitncnn_9 1 2 477 477_splitncnn_0 477_splitncnn_1 Convolution 478 1 1 477_splitncnn_1 479 0=96 1=1 5=1 6=3840 HardSwish 485 1 1 479 485 0=1.666667e-01 ConvolutionDepthWise 486 1 1 485 487 0=96 1=3 4=1 5=1 6=864 7=96 HardSwish 493 1 1 487 493 0=1.666667e-01 Convolution 494 1 1 493 495 0=40 1=1 5=1 6=3840 BinaryOp 496 2 1 477_splitncnn_0 495 496 Convolution 497 1 1 496 498 0=240 1=1 5=1 6=9600 HardSwish 504 1 1 498 504 0=1.666667e-01 ConvolutionDepthWise 505 1 1 504 506 0=240 1=3 4=1 5=1 6=2160 7=240 HardSwish 512 1 1 506 512 0=1.666667e-01 Split splitncnn_10 1 2 512 512_splitncnn_0 512_splitncnn_1 Pooling 513 1 1 512_splitncnn_1 513 0=1 4=1 InnerProduct 514 1 1 513 515 0=60 1=1 2=14400 9=1 InnerProduct 516 1 1 515 516 0=240 1=1 2=14400 BinaryOp 518 1 1 516 518 0=2 1=1 2=1.200000e+00 HardSigmoid 523 1 1 518 523 0=1.666667e-01 BinaryOp 524 2 1 512_splitncnn_0 523 524 0=2 Convolution 525 1 1 524 526 0=56 1=1 5=1 6=13440 Split splitncnn_11 1 2 526 526_splitncnn_0 526_splitncnn_1 Convolution 527 1 1 526_splitncnn_1 528 0=336 1=1 5=1 6=18816 HardSwish 534 1 1 528 534 0=1.666667e-01 ConvolutionDepthWise 535 1 1 534 536 0=336 1=3 4=1 5=1 6=3024 7=336 HardSwish 542 1 1 536 542 0=1.666667e-01 Split splitncnn_12 1 2 542 542_splitncnn_0 542_splitncnn_1 Pooling 543 1 1 542_splitncnn_1 543 0=1 4=1 InnerProduct 544 1 1 543 545 0=84 1=1 2=28224 9=1 InnerProduct 546 1 1 545 546 0=336 1=1 2=28224 BinaryOp 548 1 1 546 548 0=2 1=1 2=1.200000e+00 HardSigmoid 553 1 1 548 553 0=1.666667e-01 BinaryOp 554 2 1 542_splitncnn_0 553 554 0=2 Convolution 555 1 1 554 556 0=56 1=1 5=1 6=18816 BinaryOp 557 2 1 526_splitncnn_0 556 557 Convolution 558 1 1 557 559 0=336 1=1 5=1 6=18816
HardSwish 565 1 1 559 565 0=1.666667e-01
ConvolutionDepthWise 566 1 1 565 567 0=336 1=5 13=2 4=2 5=1 6=8400 7=336
HardSwish 573 1 1 567 573 0=1.666667e-01
Split splitncnn_13 1 2 573 573_splitncnn_0 573_splitncnn_1
Pooling 574 1 1 573_splitncnn_1 574 0=1 4=1
InnerProduct 575 1 1 574 576 0=84 1=1 2=28224 9=1
InnerProduct 577 1 1 576 577 0=336 1=1 2=28224
BinaryOp 579 1 1 577 579 0=2 1=1 2=1.200000e+00
HardSigmoid 584 1 1 579 584 0=1.666667e-01
BinaryOp 585 2 1 573_splitncnn_0 584 585 0=2
Convolution 586 1 1 585 587 0=80 1=1 5=1 6=26880
Split splitncnn_14 1 2 587 587_splitncnn_0 587_splitncnn_1
Convolution 588 1 1 587_splitncnn_1 589 0=480 1=1 5=1 6=38400
HardSwish 595 1 1 589 595 0=1.666667e-01
ConvolutionDepthWise 596 1 1 595 597 0=480 1=5 4=2 5=1 6=12000 7=480
HardSwish 603 1 1 597 603 0=1.666667e-01
Split splitncnn_15 1 2 603 603_splitncnn_0 603_splitncnn_1
Pooling 604 1 1 603_splitncnn_1 604 0=1 4=1
InnerProduct 605 1 1 604 606 0=120 1=1 2=57600 9=1
InnerProduct 607 1 1 606 607 0=480 1=1 2=57600
BinaryOp 609 1 1 607 609 0=2 1=1 2=1.200000e+00
HardSigmoid 614 1 1 609 614 0=1.666667e-01
BinaryOp 615 2 1 603_splitncnn_0 614 615 0=2
Convolution 616 1 1 615 617 0=80 1=1 5=1 6=38400
BinaryOp 618 2 1 587_splitncnn_0 617 618
Split splitncnn_16 1 2 618 618_splitncnn_0 618_splitncnn_1
Convolution 619 1 1 618_splitncnn_1 620 0=480 1=1 5=1 6=38400
HardSwish 626 1 1 620 626 0=1.666667e-01
ConvolutionDepthWise 627 1 1 626 628 0=480 1=5 4=2 5=1 6=12000 7=480
HardSwish 634 1 1 628 634 0=1.666667e-01
Split splitncnn_17 1 2 634 634_splitncnn_0 634_splitncnn_1
Pooling 635 1 1 634_splitncnn_1 635 0=1 4=1
InnerProduct 636 1 1 635 637 0=120 1=1 2=57600 9=1
InnerProduct 638 1 1 637 638 0=480 1=1 2=57600
BinaryOp 640 1 1 638 640 0=2 1=1 2=1.200000e+00
HardSigmoid 645 1 1 640 645 0=1.666667e-01
BinaryOp 646 2 1 634_splitncnn_0 645 646 0=2
Convolution 647 1 1 646 648 0=80 1=1 5=1 6=38400
BinaryOp 649 2 1 618_splitncnn_0 648 649
Convolution 650 1 1 649 651 0=480 1=1 5=1 6=38400
HardSwish 657 1 1 651 657 0=1.666667e-01
Pooling 658 1 1 657 658 1=2 2=2 5=1
Permute 659 1 1 658 659 0=4
Squeeze 660 1 1 659 660 -23300=1,3
LSTM 722 1 1 660 722 0=96 1=368640 2=2
InnerProduct 724 1 1 722 725 0=96 1=1 2=18432
Split splitncnn_18 1 2 725 725_splitncnn_0 725_splitncnn_1
Reduction 726 1 1 725_splitncnn_1 726 0=8 1=0 -23303=1,-1 4=1
Clip 727 1 1 726 727 0=1.000000e-12 1=3.402823e+38
BinaryOp 730 2 1 725_splitncnn_0 727 730 0=3
InnerProduct 737 1 1 730 737 0=6922 2=664512
BinaryOp output 1 1 737 output 0=2 1=1 2=3.000000e+01
3条答案
按热度按时间2izufjch1#
Environment
ubuntu1804 in docker
ncnn master:
commit 71bc617
Author: nihui shuizhuyuanluo@126.com
Date: Sat May 29 21:43:29 2021 +0800
nzk0hqpo2#
please provide bin file for reproducing
I tried the crnn model in https://github.com/DayBreak-u/chineseocr_lite/tree/onnx/models_ncnn and it works fine
7vux5j2d3#
please provide bin file for reproducing
I tried the crnn model in https://github.com/DayBreak-u/chineseocr_lite/tree/onnx/models_ncnn and it works fine
_crnn.zip