OpenCV Train Cascade报错VecSize not correct的技术咨询

Hey there, let's work through that "VecSize not correct" error you're facing when training your cascade classifier for blue 'X' symbols on white paper. I’ve run into this exact issue a handful of times, so here’s a step-by-step breakdown of what to check and fix:

1. Confirm sample dimension consistency across all steps #

The cascade classifier requires every positive and negative sample to be the exact same width and height. This means:

• The dimensions you specify when running Naotoshi Seo’s Perl script (likely createsamples.pl) must match the -w and -h parameters you use in your CascadeTrainer command.
• For example: If you generate samples with perl createsamples.pl -w 24 -h 24 ..., your training command must include -w 24 -h 24 — no deviations, even by one pixel.

2. Inspect the vec file’s actual dimensions #

Use OpenCV’s built-in vec2samples tool to verify what’s inside your vec file. Run this command:

vec2samples -info sample_info.txt your_generated.vec

Open the resulting sample_info.txt file and check the first line — it will list the width and height stored in the vec file. Compare these numbers directly to the -w/-h values you’re using in training. If they don’t match, that’s the root cause.

3. Double-check your Perl script parameters #

When generating your vec file with the Perl script, make sure you’re explicitly setting the width and height. A correct command looks something like this:

perl createsamples.pl -img blue_x_positive.jpg -bg negative_samples.txt -vec final_samples.vec -w 24 -h 24 -num 1000

It’s easy to overlook the -w/-h flags here, or to use values different from your training setup — that’s one of the most common causes of this error.

4. Ensure no unintended resizing mishaps #

If your original positive/negative samples have varying dimensions, the Perl script will automatically resize them to your specified -w/-h. But sometimes, manual edits to samples before running the script can throw this off. Double-check that:

• None of your input samples are corrupted or have non-standard dimensions.
• You haven’t manually resized some samples outside the script (which would create mismatches).

5. Regenerate the vec file with correct parameters #

If you find any dimension mismatches in the above steps, delete your existing vec file and re-run the Perl script with the exact width/height that matches your CascadeTrainer command. This should resolve the "VecSize not correct" error.

One quick side note for your use case: Since you’re targeting a blue 'X', make sure the Perl script isn’t converting your samples to grayscale inadvertently (some versions default to this). If you need color-based detection, you may need to tweak the script to preserve RGB channels — but fix the vec size issue first, as that’s blocking your training entirely.

内容的提问来源于stack exchange，提问作者Calvin