Visualize feature point alignment between the base image and the aligned image#86
Visualize feature point alignment between the base image and the aligned image#86ThijsVroegh wants to merge 2 commits intomainfrom
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stefsmeets
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stefsmeets
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Nice work, I left some comments in the code.
My main concern is that this is now the third different implementation of the 'detect and extract' pattern. We have src/unraphael/feature.py (skimage), src/unraphael/dash/align.py:feature_align (openCV) and now this function (skimage).
What is troubling me is that the alignment itself is using the OpenCV function, but that the display is using the skimage version without using the same parameters (e.g. the user can pick the max_ratio). And also, it uses the aligned images to find the feature points? This makes the visualization completely arbitrary, because it shows something completely different. I think the visualization should show the points and source images that are actually used in the alignment.
| def feature_based_alignment_visual( | ||
| base_image: np.ndarray, |
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I suggest protecting this function by requiring keyword arguments:
| def feature_based_alignment_visual( | |
| base_image: np.ndarray, | |
| def feature_based_alignment_visual( | |
| *, | |
| base_image: np.ndarray, |
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| Returns | ||
| ------- | ||
| None | ||
| Displays a plot showing the feature-based alignment |
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This is not necessary, but please update the function name/documentation that this will plot the aligment
| Returns | |
| ------- | |
| None | |
| Displays a plot showing the feature-based alignment |
| else: | ||
| st.error('Unsupported method selected.') | ||
| return |
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Consider raising a ValueError instead of silently failing.
| ) | ||
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| return res | ||
| return res, align_method, motion_model |
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Can we refactor this in a way that avoids returning a tuple? This makes the code difficult to maintain.
| display_in_grayscale = ( | ||
| col2.radio('Display images in:', ['Grayscale', 'Original color)']) | ||
| == 'Grayscale' | ||
| ) | ||
| # Slider to select max_ratio | ||
| max_ratio = col2.slider('Max ratio for descriptor matching', 0.5, 0.8, 0.6, 0.01) | ||
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| st.write('') | ||
| st.write('') | ||
| st.subheader(f'Feature-based alignment visualization using {motion_model}') | ||
| st.write('') |
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I think this should be in the widget.
| with col1: | ||
| st.button('⏮️ Previous', on_click=previous_image) | ||
| with col3: | ||
| st.button('Next ⏭️', on_click=next_image) |
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Nice to have: sync these buttons with those from the comparison itself.
| def next_image(): | ||
| st.session_state.image_index = (st.session_state.image_index + 1) % len(images) | ||
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| def previous_image(): | ||
| st.session_state.image_index = (st.session_state.image_index - 1) % len(images) |
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Nice to have: We use this pattern now in several places. Can we refactor/generalize it so that we avoid this code duplication everywhere?
| def display_current_image(): | ||
| current_image = images[st.session_state.image_index] | ||
| feature_based_alignment_visual( | ||
| base_image=base_image.data, | ||
| target_image=current_image.data, | ||
| method=method, | ||
| base_image_name=base_image.name, | ||
| target_image_name=current_image.name, | ||
| display_in_grayscale=display_in_grayscale, | ||
| max_ratio=max_ratio, | ||
| ) |
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Does this need to be a function?
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This PR adds the option to the alignment page to visualize the feature point alignment between the base image and the aligned image. This is helpful because it allows to evaluate whether the feature based alignment is suited for the alignment of the data used.