LoginSignup
9
5

More than 3 years have passed since last update.

@yka2ki

PrototxtとCaffemodelって何だ？

Last updated at Posted at 2019-03-10

Memo

Darknet/Yoloのモデルや重みデータを、prototxt、caffemodelに変換したいので調べてます。

やりたい事はつまり、Tsingjinyunの説明を引用しますと、

「Darknet configuration file .cfg to the .prototxt definition in Caffe, a tool to convert the weight file .weights to .caffemodel in Caffe and a detection demo to test the converted networks.」

Convert Darknet model to Caffe's

検索すると、関係するリンクが集められたサイトがあった。その中のリンクを含め片っ端から調べてみる。

Tsingjinyun/Caffe-YOLO2

This is a set of tools to convert models from Darknet to Caffe, and in particular to convert the YOLO networks for object detection. For more details, see the paper:

手当たり次第、cfgとweightsを使って実行してみた。まずcfgからprototxtへの変換。

darknet
# python create_yolo_prototxt.py ../darknet_cfg-weights/darknet.cfg darknet
WARNING: cost layer not recognized
tiny
# python create_yolo_prototxt.py ../darknet_cfg-weights/tiny.cfg tiny
WARNING: cost layer not recognized
yolov2-tiny-voc
# python create_yolo_prototxt.py ../darknet_cfg-weights/yolov2-tiny-voc.cfg yolov2-tiny-voc
WARNING: region layer not recognized
yolov2-tiny
# python create_yolo_prototxt.py ../darknet_cfg-weights/yolov2-tiny.cfg yolov2-tiny
WARNING: region layer not recognized
yolov2-voc
# python create_yolo_prototxt.py ../darknet_cfg-weights/yolov2-voc.cfg yolov2-voc
WARNING: route layer not recognized
WARNING: reorg layer not recognized
WARNING: route layer not recognized
WARNING: region layer not recognized
yolov2
# python create_yolo_prototxt.py ../darknet_cfg-weights/yolov2.cfg yolov2
WARNING: route layer not recognized
WARNING: reorg layer not recognized
WARNING: route layer not recognized
WARNING: region layer not recognized
yolov3
# python create_yolo_prototxt.py ../darknet_cfg-weights/yolov3.cfg yolov3
WARNING: shortcut layer not recognized
WARNING: shortcut layer not recognized
～
WARNING: shortcut layer not recognized
WARNING: shortcut layer not recognized
WARNING: yolo layer not recognized
WARNING: route layer not recognized
WARNING: upsample layer not recognized
WARNING: route layer not recognized
WARNING: yolo layer not recognized
WARNING: route layer not recognized
WARNING: upsample layer not recognized
WARNING: route layer not recognized
WARNING: yolo layer not recognized
results
# ls -l *.prototxt
-rw-r--r-- 1 root root  5768 Mar 22 15:13 darknet_deploy.prototxt
-rw-r--r-- 1 root root 10257 Mar 22 15:14 tiny_deploy.prototxt
-rw-r--r-- 1 root root  6027 Mar 22 13:12 yolov2-tiny-voc_deploy.prototxt
-rw-r--r-- 1 root root  6026 Mar 22 13:13 yolov2-tiny_deploy.prototxt
-rw-r--r-- 1 root root 14500 Mar 22 13:13 yolov2-voc_deploy.prototxt
-rw-r--r-- 1 root root 14500 Mar 22 13:13 yolov2_deploy.prototxt
-rw-r--r-- 1 root root 44915 Mar 22 13:13 yolov3_deploy.prototxt

できたprototxtを使い、weightsをcaffemodelへ変換。

darknet
# python create_yolo_caffemodel.py \
darknet_deploy.prototxt ../darknet_cfg-weights/darknet.weights \
darknet.caffemodel

model file is darknet_deploy.prototxt
weight file is ../darknet_cfg-weights/darknet.weights
output caffemodel file is darknet.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv7
  converting conv8
Converted 7323480 weights.
tiny
# python create_yolo_caffemodel.py \
tiny_deploy.prototxt ../darknet_cfg-weights/tiny.weights \
tiny.caffemodel

model file is tiny_deploy.prototxt
weight file is ../darknet_cfg-weights/tiny.weights
output caffemodel file is tiny.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv15
  converting conv16
Converted 1046488 weights.
yolov2-tiny-voc
# python create_yolo_caffemodel.py \
yolov2-tiny-voc_deploy.prototxt ../darknet_cfg-weights/yolov2-tiny-voc.weights \
yolov2-tiny-voc.caffemodel

model file is yolov2-tiny-voc_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov2-tiny-voc.weights
output caffemodel file is yolov2-tiny-voc.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv8
  converting conv9
Converted 15867885 weights.
yolov2-tiny
# python create_yolo_caffemodel.py \
yolov2-tiny_deploy.prototxt ../darknet_cfg-weights/yolov2-tiny.weights \
yolov2-tiny.caffemodel

model file is yolov2-tiny_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov2-tiny.weights
output caffemodel file is yolov2-tiny.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv8
  converting conv9
Traceback (most recent call last):
  File "create_yolo_caffemodel.py", line 115, in <module>
    main()
  File "create_yolo_caffemodel.py", line 111, in main
    convert_weights(args.model, args.yolo_weights, args.output)
  File "create_yolo_caffemodel.py", line 94, in convert_weights
    format(weights.size, count, weights.size-count))
ValueError:  Wrong number of weights: read 11237146, used 11237145 (missing 1)
yolov2-voc
# python create_yolo_caffemodel.py \
yolov2-voc_deploy.prototxt ../darknet_cfg-weights/yolov2-voc.weights \
yolov2-voc.caffemodel

model file is yolov2-voc_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov2-voc.weights
output caffemodel file is yolov2-voc.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv22
  converting conv23
Traceback (most recent call last):
  File "create_yolo_caffemodel.py", line 115, in <module>
    main()
  File "create_yolo_caffemodel.py", line 111, in main
    convert_weights(args.model, args.yolo_weights, args.output)
  File "create_yolo_caffemodel.py", line 94, in convert_weights
    format(weights.size, count, weights.size-count))
ValueError:  Wrong number of weights: read 50676062, used 39502173 (missing 11173889)
yolov2-tiny
# python create_yolo_caffemodel.py \
yolov2-tiny_deploy.prototxt ../darknet_cfg-weights/yolov2-tiny.weights \
yolov2-tiny.caffemodel

model file is yolov2-tiny_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov2-tiny.weights
output caffemodel file is yolov2-tiny.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv8
  converting conv9
Traceback (most recent call last):
  File "create_yolo_caffemodel.py", line 115, in <module>
    main()
  File "create_yolo_caffemodel.py", line 111, in main
    convert_weights(args.model, args.yolo_weights, args.output)
  File "create_yolo_caffemodel.py", line 94, in convert_weights
    format(weights.size, count, weights.size-count))
ValueError:  Wrong number of weights: read 11237146, used 11237145 (missing 1)
yolov2
# python create_yolo_caffemodel.py \
yolov2_deploy.prototxt ../darknet_cfg-weights/yolov2.weights \
yolov2.caffemodel

model file is yolov2_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov2.weights
output caffemodel file is yolov2.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv22
  converting conv23
Traceback (most recent call last):
  File "create_yolo_caffemodel.py", line 115, in <module>
    main()
  File "create_yolo_caffemodel.py", line 111, in main
    convert_weights(args.model, args.yolo_weights, args.output)
  File "create_yolo_caffemodel.py", line 94, in convert_weights
    format(weights.size, count, weights.size-count))
ValueError:  Wrong number of weights: read 50983561, used 39809673 (missing 11173888)
yolov3
# python create_yolo_caffemodel.py \
yolov3_deploy.prototxt ../darknet_cfg-weights/yolov3.weights \
yolov3.caffemodel

model file is yolov3_deploy.prototxt
weight file is ../darknet_cfg-weights/yolov3.weights
output caffemodel file is yolov3.caffemodel
Transpose fc layers: False
  converting conv1
  converting conv2
　～
  converting conv74
  converting conv75
Traceback (most recent call last):
  File "create_yolo_caffemodel.py", line 115, in <module>
    main()
  File "create_yolo_caffemodel.py", line 111, in main
    convert_weights(args.model, args.yolo_weights, args.output)
  File "create_yolo_caffemodel.py", line 94, in convert_weights
    format(weights.size, count, weights.size-count))
ValueError:  Wrong number of weights: read 62001758, used 61771997 (missing 229761)

できたのは、yolov2-tiny-vocだけ。

results
# ls -l *.caffemodel
-rw-r--r-- 1 root root 29296614 Mar 22 15:17 darknet.caffemodel
-rw-r--r-- 1 root root  4191062 Mar 22 15:17 tiny.caffemodel
-rw-r--r-- 1 root root 63474427 Mar 22 13:18 yolov2-tiny-voc.caffemodel

READMEに従い、できあがったprototxtとcaffemodelを使って、Caffeで動かして確認する。

# python yolo_detect.py \
　darknet_deploy.prototxt darknet.caffemodel \
　images/dog.jpg

エラーを吐いて実行できず。
このGitにある元々のファイルを使うと、tiny-yoloだけOKだった。

# python yolo_detect.py \
　prototxt_caffemodel/tiny_yolo_deploy.prototxt　prototxt_caffemodel/tiny_yolo.caffemodel \
　images/dog.jpg

深追いは止めて、一先ずここまでにしておく:thermometer_face:

Pushyami/YOLOv3-Caffe

Pytorchで、スクラッチからYOLOv3を実装する方法ということらしく、「オブジェクト検出の学習に取り組むための最善の方法は、最初からアルゴリズムを自分で実装すること」と書かれていました。

Part1

YOLOのしくみ、層の説明があり、参考になるかな。

Part2

YOLOのcfg（つまりCaffeのprototxt）の簡単な説明がある。YOLOで使用されるレイヤは、Convolutional、Shortcut、Upsample、Route、YOLO（検知層）の5種類だそうな。

Part3

Pytorchでの実装に入ってくるので、ビギナーにはつらいな～:frowning2:

Part4
Part5

Jasonlovescoding/YOLOv3-Caffe

CaffeでYolov3を動かしているみたい。
prototxtとcaffemodelをGoogleDriveからダウンロードできたので、Netronで見てみると、100ぐらいの隠れ層があって、とっても深～い！Netronの表示結果は　ここ　をクリック。

Python3のCaffeが必要みたい、良くわからないので断念:sob:

ChenYingpeng/Caffe-YOLOv3

こちらはBaidouにprototxt/caffemodel、cfg/weightsがUpされているが、Baidouのアプリをインストールしないといけないようで、怖いから止めとこ:relaxed:

Marvis/Pytorch-Caffe-Darknet-convert

Pytorch、Caffe、DarknetのConvert、これもPytorchが要る。

# python darknet2caffe.py \
  ../darknet_Cfg-Weights/tiny-yolo-voc.cfg \
  ../darknet_Cfg-Weights/tiny-yolo-voc.weights \
  tiny-yolo-voc.prototxt tiny-yolo-voc.caffemodel
Traceback (most recent call last):
  File "darknet2caffe.py", line 6, in <module>
    from cfg import *
  File "/home/hoge/temp/darknet2caffe/Marvis_Pytorch-Caffe-Darknet/cfg.py", line 1, in <module>
    import torch
ImportError: No module named torch

仕方ない、Pytorchをインストールしてみるか:frowning2:

Ysh329/Darknet2Caffe

ysh329/darknet-to-caffe-model-convertorが元のようで、これもPytorchがいるみたい:thinking:

Ysh329/Darknet2Caffe
root@3034bee841db:~/darknet2caffe# ./convert_YOLOv2_fromDarknet2Caffe.sh 
Traceback (most recent call last):
  File "darknet2caffe.py", line 5, in <module>
    from cfg import *
  File "/root/darknet2caffe/cfg.py", line 1, in <module>
    import torch
ImportError: No module named torch
root@3034bee841db:~/darknet2caffe#

Xingwangsfu/Caffe-YOLO

This is a caffe implementation of the YOLO

まだ試していない・・・

Lwplw/Darknet2Caffe

まだ試していない・・・

Xilinx/ML-Suite

まだ試していない・・・

Abars/Darknet2Caffe

これもPytorchが必要みたい:rolling_eyes:

Traceback (most recent call last):
  File "./darknet2caffe27.py", line 6, in <module>
    from cfg import *
  File "/home/hoge/temp/caffe-ssd/python/darknet2caffe/cfg.py", line 1, in <module>
    import torch
ImportError: No module named torch

README.mdを見てみたら書いてあった。

This repository is forked from pytorch-caffe-darknet-convert.

karolmajek/darknet

4KのVideo入力を、Tiny YOLOで認識しているらしい・・・　4K Tiny YOLO Object Detection

prototxtとcaffemodelって何だ？

ネットワークモデルの定義、重みファイルについて・・・

Caffeの実装理解のために

Caffeの学習済みモデルの利用

株式会社グリッドの、ReNoMという機械学習フレームワークのチュートリアルページに辿り着いた。

Caffe: Tutorial: Blob, 層, そしてネット : Caffe モデルの解剖

株式会社クラスキャットの、Caffeの本家サイトのTutorial – Blobs, Layers, and Nets: anatomy of a Caffe modelを翻訳・補足したページに辿り着いた。

Caffeを通してCNNを理解する #1

Caffeを通してCNNを理解する #2

Caffeによるシーン認識(8分類問題)

Seiya.Kumadaさんのブログ

YOLOv3の使い方

Seiya.Kumadaさんのブログ

prototxtの可視化

How do you visualize neural network architectures?

に投稿されていたものの中から、

Netron

Netscope

Ubuntu16.04, Docker, Caffe

こちらへ

取り敢えず、ここまで。

9
5
0

Register as a new user and use Qiita more conveniently

  1. You get articles that match your needs
  2. You can efficiently read back useful information
  3. You can use dark theme
What you can do with signing up
Sign upLogin
9
5