扩充了训练样本，训练出的SVM模型将所有图片都判别为非车牌

Description

Contributor guide

Tech stack

cpp

Domain

machine learningai

Issue type

bug

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

4

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

half day

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

stale

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

mostly clear

Prerequisites

SVMOpenCVC++image processing

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

15

Research direction

The issue is that adding more training samples caused the SVM model to classify all images as non plate. Investigate the training script (likely in src/train) and verify the labels and preprocessing steps. Consider using a validation set to detect overfitting and check if new samples have different distribution than original ones.