dvsseed

classes= 12
train  = /home/user/darknet/drug_detect/drug_train.txt
valid  = /home/user/darknet/drug_detect/drug_val.txt
names  = /home/user/darknet/drug_detect/drug_voc.names
backup = /home/user/darknet/drug_detect/backup/

dvsseed

import xml.etree.ElementTree as ET
import pickle
import os
from os import listdir, getcwd
from os.path import join

# 這裡改[類別名稱]，drug的項目有12個類別
classes = ["Binin-U", "Concor5mg", "Depyretin", "Diphenidol", "ligilin", "Lopedin", "Madopar125mg", "Madopar250mg", "Medicon-A", "Requip025", "spironolactone", "Treceton"]

dvsseed

Binin-U
Concor5mg
Depyretin
Diphenidol
ligilin
Lopedin
Madopar125mg
Madopar250mg
Medicon-A
Requip025

dvsseed

name: "AlexNet"
layer {
  name: "data"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {

dvsseed

net: "train_val.prototxt"
test_iter: 1000
test_interval: 1000
base_lr: 0.01
lr_policy: "step"
gamma: 0.1
stepsize: 10000
display: 20
# max_iter: 450000
max_iter: 50200

dvsseed

name: "AlexNet"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param { shape: { dim: 1 dim: 3 dim: 135 dim: 135 } }
}
layer {
  name: "conv1"
  type: "Convolution"

dvsseed

@echo off

SET DIRD="C:\Users\user\caffe-windows"

FOR /L %%G IN (0,1,11) DO FOR %%i IN (%%G\*.*) DO %DIRD%\Build\x64\Release\classification.exe deploy.prototxt caffe_alexnet_train_iter_30000.caffemodel mean.binaryproto label_12.txt %%i

pause

dvsseed

@echo off

SET FILE="caffe_alexnet_train_iter_30000.solverstate"
SET DIRD="C:\Users\user\caffe-windows"

IF EXIST %FILE% (
  REM Resuming
  %DIRD%\Build\x64\Release\caffe.exe train --solver=solver.prototxt --snapshot=%FILE% -gpu 0
) ELSE (
  REM Training

dvsseed

@echo off

SET DIRD="C:\Users\user\caffe-windows"
%DIRD%\Build\x64\Release\compute_image_mean.exe train_all_lmdb mean.binaryproto

pause

dvsseed

@echo off

SET DIRC="test_all_lmdb"
IF EXIST %DIRC% (
  RMDIR /S /Q %DIRC%
)

SET DIRD="C:\Users\user\caffe-windows"
%DIRD%\Build\x64\Release\convert_imageset.exe %DIRD%\dataset\ test.txt %DIRC% --gray=false --shuffle=false --resize_width=180 --resize_height=135 --check_size=false --encode_type=jpg