Loading notebooks/AdaptiveNon-MaximalSuppressionDemonstration.ipynbdeleted 100644 → 0 +0 −80 Original line number Diff line number Diff line %% Cell type:code id: tags: ``` python import os import sys sys.path.insert(0, os.path.abspath('..')) from autocnet.examples import get_path from autocnet.graph.network import CandidateGraph from autocnet.matcher.matcher import FlannMatcher from IPython.display import display %pylab qt4 ``` %% Output Populating the interactive namespace from numpy and matplotlib %% Cell type:code id: tags: ``` python serial_numbers = {'AS15-M-0295_SML.png': '1971-07-31T01:24:11.754', 'AS15-M-0296_SML.png': '1971-07-31T01:24:36.970', 'AS15-M-0297_SML.png': '1971-07-31T01:25:02.243', 'AS15-M-0298_SML.png': '1971-07-31T01:25:27.457', 'AS15-M-0299_SML.png': '1971-07-31T01:25:52.669', 'AS15-M-0300_SML.png': '1971-07-31T01:26:17.923'} for k, v in serial_numbers.items(): serial_numbers[k] = 'APOLLO15/METRIC/{}'.format(v) ``` %% Cell type:code id: tags: ``` python adjacency = get_path('two_image_adjacency.json') basepath = get_path('Apollo15') cg = CandidateGraph.from_adjacency(adjacency, basepath=basepath) cg.plot() ``` %% Output <matplotlib.axes._subplots.AxesSubplot at 0x7fabc74fe630> %% Cell type:code id: tags: ``` python cg.extract_features(method='sift', extractor_parameters={"nfeatures":500}) ``` %% Cell type:code id: tags: ``` python for i, node in cg.nodes_iter(data=True): node.anms(nfeatures=100) ``` %% Cell type:markdown id: tags: The even and odd figure numbers can be blinked to see pre- and post-ANMS keypoints. %% Cell type:code id: tags: ``` python for i, node in cg.nodes_iter(data=True): figure(i) node.plot() plt.title(node.image_name + ': Before ANMS') figure(i+2) node.plot(clean_keys=['anms']) plt.title(node.image_name + ': After ANMS') ``` %% Cell type:code id: tags: ``` python ``` Loading
notebooks/AdaptiveNon-MaximalSuppressionDemonstration.ipynbdeleted 100644 → 0 +0 −80 Original line number Diff line number Diff line %% Cell type:code id: tags: ``` python import os import sys sys.path.insert(0, os.path.abspath('..')) from autocnet.examples import get_path from autocnet.graph.network import CandidateGraph from autocnet.matcher.matcher import FlannMatcher from IPython.display import display %pylab qt4 ``` %% Output Populating the interactive namespace from numpy and matplotlib %% Cell type:code id: tags: ``` python serial_numbers = {'AS15-M-0295_SML.png': '1971-07-31T01:24:11.754', 'AS15-M-0296_SML.png': '1971-07-31T01:24:36.970', 'AS15-M-0297_SML.png': '1971-07-31T01:25:02.243', 'AS15-M-0298_SML.png': '1971-07-31T01:25:27.457', 'AS15-M-0299_SML.png': '1971-07-31T01:25:52.669', 'AS15-M-0300_SML.png': '1971-07-31T01:26:17.923'} for k, v in serial_numbers.items(): serial_numbers[k] = 'APOLLO15/METRIC/{}'.format(v) ``` %% Cell type:code id: tags: ``` python adjacency = get_path('two_image_adjacency.json') basepath = get_path('Apollo15') cg = CandidateGraph.from_adjacency(adjacency, basepath=basepath) cg.plot() ``` %% Output <matplotlib.axes._subplots.AxesSubplot at 0x7fabc74fe630> %% Cell type:code id: tags: ``` python cg.extract_features(method='sift', extractor_parameters={"nfeatures":500}) ``` %% Cell type:code id: tags: ``` python for i, node in cg.nodes_iter(data=True): node.anms(nfeatures=100) ``` %% Cell type:markdown id: tags: The even and odd figure numbers can be blinked to see pre- and post-ANMS keypoints. %% Cell type:code id: tags: ``` python for i, node in cg.nodes_iter(data=True): figure(i) node.plot() plt.title(node.image_name + ': Before ANMS') figure(i+2) node.plot(clean_keys=['anms']) plt.title(node.image_name + ': After ANMS') ``` %% Cell type:code id: tags: ``` python ```