onnx convertor

[georgeokelly]

When I convert yolov2-tiny-voc.onnx to param and bin, it says

Pad not supported yet!
  # mode=edge
  # pads 7

and the onnx model is exported from pytorch model .
BTW, the yolo cfg is like this:

[net]

# Testing

batch=64

subdivisions=8

# Training

# batch=64

# subdivisions=8

height=416

width=416

channels=3

momentum=0.9

decay=0.0005

angle=0

saturation = 1.5

exposure = 1.5

hue=.1



learning_rate=0.001

burn_in=1000

max_batches = 80200

policy=steps

steps=-1,500,40000,60000

scales=0.1,10,.1,.1



[convolutional]

batch_normalize=1

filters=32

size=3

stride=1

pad=1

activation=leaky



[maxpool]

size=2

stride=2



[convolutional]

batch_normalize=1

filters=64

size=3

stride=1

pad=1

activation=leaky



[maxpool]

size=2

stride=2



[convolutional]

batch_normalize=1

filters=128

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=64

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=128

size=3

stride=1

pad=1

activation=leaky



[maxpool]

size=2

stride=2



[convolutional]

batch_normalize=1

filters=256

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=128

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=256

size=3

stride=1

pad=1

activation=leaky



[maxpool]

size=2

stride=2



[convolutional]

batch_normalize=1

filters=512

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=256

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=512

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=256

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=512

size=3

stride=1

pad=1

activation=leaky



[maxpool]

size=2

stride=2



[convolutional]

batch_normalize=1

filters=1024

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=512

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=1024

size=3

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=512

size=1

stride=1

pad=1

activation=leaky



[convolutional]

batch_normalize=1

filters=1024

size=3

stride=1

pad=1

activation=leaky





#######



[convolutional]

batch_normalize=1

size=3

stride=1

pad=1

filters=1024

activation=leaky



[convolutional]

batch_normalize=1

size=3

stride=1

pad=1

filters=1024

activation=leaky



[route]

layers=-9



[convolutional]

batch_normalize=1

size=1

stride=1

pad=1

filters=64

activation=leaky



[reorg]

stride=2



[route]

layers=-1,-4



[convolutional]

batch_normalize=1

size=3

stride=1

pad=1

filters=1024

activation=leaky



[convolutional]

size=1

stride=1

pad=1

filters=125

activation=linear

[nihui]

针对onnx模型转换的各种问题，推荐使用最新的pnnx工具转换到ncnn
In view of various problems in onnx model conversion, it is recommended to use the latest pnnx tool to convert to ncnn

pip install pnnx
pnnx model.onnx inputshape=[1,3,224,224]

详细参考文档
Detailed reference documentation
https://github.com/pnnx/pnnx
https://github.com/Tencent/ncnn/wiki/use-ncnn-with-pytorch-or-onnx#how-to-use-pnnx