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Dmitrii Tarasov
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add colorization and b channel suppression exapmles and eigenvalues exaamples
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project/index.html

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@@ -168,20 +168,36 @@ <h2 class="title is-3" style="white-space: nowrap;">Reconstruct images from feat
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<div class="columns is-centered has-text-centered">
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations</h2>
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations. Q matrix Calculation and Application.</h2>
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<img src="./static/images/features_reconstruction_manipulation_train_Q.drawio.png" alt="features_reconstruction_manipulation_train_Q" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 3. Feature-space transformations. Q matrix Calculation.</b> We then calculate Q matrix for feature-space manupulation.
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</p>
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<img src="./static/images/features_reconstruction_manipulation.drawio.png" alt="features_reconstruction_manipulation" width="900">
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<img src="./static/images/features_reconstruction_manipulation_eval_Q.drawio.png" alt="features_reconstruction_manipulation_eval_Q" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 3. Feature-space transformations.</b> We then calculate Q matrix for feature-space manupulation.
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<b>Figure 4. Feature-space transformations. Q matrix Application.</b> After Q matrix is calculated, we apply it to the feature space. For each patch embedding.
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations. Color Swap Examples.</h2>
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<img src="./static/images/rb_swap.png" alt="rb_swap" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 4. Red-blue channel swap samples.</b> We then calculate Q matrix for feature-space manupulation.
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<b>Figure 5. Red-blue channel swap samples.</b>
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<img src="./static/images/rb_swap_eigenvalues.png" alt="rb_swap_eigenvalues" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 5. Eigenvalues for red-blue channel swap matrix.</b> Majority of eigenvalues are close to 1, which means that the transformation is close to an identity matrix. While the other cluster of eigenvalues are close to -1, which means that for these channels direction is changed to the opposite.
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<b>Figure 6. Eigenvalues for red-blue channel swap matrix.</b> Majority of eigenvalues are close to 1, which means that the transformation is close to an identity matrix. While the other cluster of eigenvalues are close to -1, which means that for these channels direction is changed to the opposite.
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations. Blue Channel Suppression.</h2>
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<img src="./static/images/b_suppression_all_transformations.png" alt="b_suppression_all_transformations" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 7. Blue channel suppression samples.</b>
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</p>
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<img src="./static/images/b_suppression_all_eigen_values.png" alt="b_suppression_all_eigen_values" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 8. Eigenvalues for blue channel suppression matrix.</b>
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<h2 class="title is-3" style="white-space: nowrap;">Feature-space transformations. Colorization.</h2>
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<img src="./static/images/colorized_examples.png" alt="colorization_all_transformations" width="900">
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<p class="caption" style="width: 100%; text-align: center;">
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<b>Figure 9. Colorization samples.</b>
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</p>
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<br><br>
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