如何调整yolo混淆矩阵的大小，使其更加美观

1、找到xxx/utils/metrics.py
2、找到这个函数

3、往下拉找到这里，自己对照改一下

		import seaborn as sn

        array = self.matrix / ((self.matrix.sum(0).reshape(1, -1) + 1E-9) if normalize else 1)  # normalize columns
        array[array < 0.005] = np.nan  # don't annotate (would appear as 0.00)

        fig, ax = plt.subplots(1, 1, figsize=(12, 9), tight_layout=True)
        nc, nn = self.nc, len(names)  # number of classes, names
        sn.set(font_scale=2.0 if nc < 50 else 0.8)  # for label size
        labels = (0 < nn < 99) and (nn == nc)  # apply names to ticklabels
        ticklabels = (list(names) + ['background']) if labels else 'auto'
        with warnings.catch_warnings():
            warnings.simplefilter('ignore')  # suppress empty matrix RuntimeWarning: All-NaN slice encountered
            sn.heatmap(array,
                       ax=ax,
                       annot=nc < 30,
                       annot_kws={
                           'size': 20},
                       cmap='Blues',
                       fmt='.2f' if normalize else '.0f',
                       square=True,
                       vmin=0.0,
                       xticklabels=ticklabels,
                       yticklabels=ticklabels).set_facecolor((1, 1, 1))
        plt.xticks(fontsize=15)
        plt.yticks(fontsize=15)

        title = 'Confusion Matrix' + ' Normalized' * normalize
        ax.set_xlabel('True',fontsize=20)
        ax.set_ylabel('Predicted',fontsize=20)
        ax.set_title(title,fontsize=20)
        plot_fname = Path(save_dir) / f'{title.lower().replace(" ", "_")}.png'
        fig.savefig(plot_fname, dpi=500)
        plt.close(fig)
        if on_plot:
            on_plot(plot_fname)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35

效果图：