我在使用 PASCAL 开发套件和由 Felzenszwalb、D. McAllester、D. Ramaman 和他的团队在 Matlab 中实现的经过判别训练的可变形零件模型系统来训练模型时遇到问题。
目前，当我尝试使用 10 个正图像和 10 个负图像为“猫”训练一个 1 分量模型时出现此输出错误。
Error:
??? Index exceeds matrix dimensions.
Error in ==> pascal_train at 48
models{i} = train(cls, models{i}, spos{i}, neg(1:maxneg),
0, 0, 4, 3, ...
Error in ==> pascal at 28
model = pascal_train(cls, n, note);
这是 pascal_train 文件
function model = pascal_train(cls, n, note)
% model = pascal_train(cls, n, note)
% Train a model with 2*n components using the PASCAL dataset.
% note allows you to save a note with the trained model
% example: note = 'testing FRHOG (FRobnicated HOG)
% At every "checkpoint" in the training process we reset the
% RNG's seed to a fixed value so that experimental results are
% reproducible.
initrand();
if nargin < 3
note = '';
end
globals;
[pos, neg] = pascal_data(cls, true, VOCyear);
% split data by aspect ratio into n groups
spos = split(cls, pos, n);
cachesize = 24000;
maxneg = 200;
% train root filters using warped positives & random negatives
try
load([cachedir cls '_lrsplit1']);
catch
initrand();
for i = 1:n
% split data into two groups: left vs. right facing instances
models{i} = initmodel(cls, spos{i}, note, 'N');
inds = lrsplit(models{i}, spos{i}, i);
models{i} = train(cls, models{i}, spos{i}(inds), neg, i, 1, 1, 1, ...
cachesize, true, 0.7, false, ['lrsplit1_' num2str(i)]);
end
save([cachedir cls '_lrsplit1'], 'models');
end
% train root left vs. right facing root filters using latent detections
% and hard negatives
try
load([cachedir cls '_lrsplit2']);
catch
initrand();
for i = 1:n
models{i} = lrmodel(models{i});
models{i} = train(cls, models{i}, spos{i}, neg(1:maxneg), 0, 0, 4, 3, ...
cachesize, true, 0.7, false, ['lrsplit2_' num2str(i)]);
end
save([cachedir cls '_lrsplit2'], 'models');
end
% merge models and train using latent detections & hard negatives
try
load([cachedir cls '_mix']);
catch
initrand();
model = mergemodels(models);
48: model = train(cls, model, pos, neg(1:maxneg), 0, 0, 1, 5, ...
cachesize, true, 0.7, false, 'mix');
save([cachedir cls '_mix'], 'model');
end
% add parts and update models using latent detections & hard negatives.
try
load([cachedir cls '_parts']);
catch
initrand();
for i = 1:2:2*n
model = model_addparts(model, model.start, i, i, 8, [6 6]);
end
model = train(cls, model, pos, neg(1:maxneg), 0, 0, 8, 10, ...
cachesize, true, 0.7, false, 'parts_1');
model = train(cls, model, pos, neg, 0, 0, 1, 5, ...
cachesize, true, 0.7, true, 'parts_2');
save([cachedir cls '_parts'], 'model');
end
save([cachedir cls '_final'], 'model');
我在第 48 行突出显示了错误发生的代码行。
我很确定系统正在读取正面和负面图像以进行正确训练。我不知道这个错误发生在哪里，因为 matlab 没有准确指出哪个索引超出了矩阵维度。
如果我在某处做错了，我试图尽可能地整理代码。
我应该从哪里开始寻找任何建议？
好的，我尝试使用 display 来检查 pascal_train 使用的变量；显示（一）；显示（尺寸（型号））；显示（大小（spos））；显示（长度（负））；显示（最大）；
所以返回的结果是；
1
1 1
1 1
10
200