[DL]深度学习中的模型可视化工具，支持ONNX, Caffe, Keras, Darknet, pytorch, TensorFlow目前格式最全！！！！-马春杰杰

文章目录

学习深度学习，经常会遇到一个问题，那就是如何对深度学习的模型进行可视化，以yolo为例，这是yolov2-tiny-voc.cfg 的配置文件：

[net]
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=2
width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[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

[maxpool]
size=2
stride=2

[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

[maxpool]
size=2
stride=1

[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]
size=1
stride=1
pad=1
filters=125
activation=linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match=1
classes=20
coords=4
num=5
softmax=1
jitter=.2
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .6
random=1

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[net]

# Testing

batch=1

subdivisions=1

# Training

# batch=64

# subdivisions=2

width=416

height=416

channels=3

momentum=0.9

decay=0.0005

angle=0

saturation = 1.5

exposure = 1.5

hue=.1

learning_rate=0.001

max_batches = 40200

policy=steps

steps=-1,100,20000,30000

scales=.1,10,.1,.1

[convolutional]

batch_normalize=1

filters=16

size=3

stride=1

pad=1

activation=leaky

[maxpool]

size=2

stride=2

[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

[maxpool]

size=2

stride=2

[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

[maxpool]

size=2

stride=1

[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]

size=1

stride=1

pad=1

filters=125

activation=linear

[region]

anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52

bias_match=1

classes=20

coords=4

num=5

softmax=1

jitter=.2

rescore=1

object_scale=5

noobject_scale=1

class_scale=1

coord_scale=1

absolute=1

thresh = .6

random=1

光看这个配置文件，我们可能很难看出它到底是怎样的结构，这时，可以祭出这个模型可视化的神器了，地址：

https://www.machunjie.com/dl/Visualization/index.html

[DL]深度学习中的模型可视化工具，支持ONNX, Caffe, Keras, Darknet, pytorch, TensorFlow目前格式最全！！！！

目前支持的格式：

ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Core ML (.mlmodel), Caffe (.caffemodel, .prototxt), Caffe2 (predict_net.pb, predict_net.pbtxt), MXNet (.model, -symbol.json), TorchScript (.pt, .pth), NCNN (.param) and TensorFlow Lite (.tflite).

PyTorch (.pt, .pth), Torch (.t7), CNTK (.model, .cntk), Deeplearning4j (.zip), PaddlePaddle (.zip, __model__), Darknet (.cfg), scikit-learn (.pkl), TensorFlow.js (model.json, .pb) and TensorFlow (.pb, .meta, .pbtxt).

远程调用：

https://www.machunjie.com/dl/Visualization/index.html?url=模型文件地址

如：https://www.machunjie.com/dl/Visualization/index.html?url=https://ibelem.github.io/webml-website/examples/image_classification/model/squeezenet1.1.onnx

[DL]深度学习中的模型可视化工具，支持ONNX, Caffe, Keras, Darknet, pytorch, TensorFlow目前格式最全！！！！