PCA visualization: add whitening and sigmoid

README.md

@@ -96,7 +96,8 @@ from sklearn.decomposition import PCA
 
 spatial = out.patch_tokens.reshape(1, 32, 32, 768)
 feat = spatial[0].detach().numpy().reshape(-1, 768)
-rgb = PCA(n_components=3).fit_transform(feat).reshape(32, 32, 3)
+rgb = PCA(n_components=3, whiten=True).fit_transform(feat).reshape(32, 32, 3)
+rgb = 1 / (1 + np.exp(-2.0 * rgb))  # sigmoid for [0, 1] range with good contrast
 print(rgb.shape)  # (32, 32, 3) — PCA of patch features as RGB
 ```