Save *.npy features on detect.py `--visualize` (#5701)

* Add feature map to save npy files

Add feature map to save npy files,export npy files with 32 feature maps per layer.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update plots.py

* Update plots.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update plots.py

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <[email protected]>

tutorial.ipynb

@@ -1104,4 +1104,4 @@
       "outputs": []
     }
   ]
-}
+}

utils/plots.py

@@ -132,7 +132,7 @@ def feature_visualization(x, module_type, stage, n=32, save_dir=Path('runs/detec
     if 'Detect' not in module_type:
         batch, channels, height, width = x.shape  # batch, channels, height, width
         if height > 1 and width > 1:
-            f = f"stage{stage}_{module_type.split('.')[-1]}_features.png"  # filename
+            f = save_dir / f"stage{stage}_{module_type.split('.')[-1]}_features.png"  # filename
 
             blocks = torch.chunk(x[0].cpu(), channels, dim=0)  # select batch index 0, block by channels
             n = min(n, channels)  # number of plots
@@ -143,9 +143,10 @@ def feature_visualization(x, module_type, stage, n=32, save_dir=Path('runs/detec
                 ax[i].imshow(blocks[i].squeeze())  # cmap='gray'
                 ax[i].axis('off')
 
-            print(f'Saving {save_dir / f}... ({n}/{channels})')
-            plt.savefig(save_dir / f, dpi=300, bbox_inches='tight')
+            print(f'Saving {f}... ({n}/{channels})')
+            plt.savefig(f, dpi=300, bbox_inches='tight')
             plt.close()
+            np.save(str(f.with_suffix('.npy')), x[0].cpu().numpy())  # npy save
 
 
 def hist2d(x, y, n=100):