Commit
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3150ada
1
Parent(s):
91b350c
separate cv_ins and cv_del + bump to 0.4
Browse files- hoho/wed.py +16 -10
- setup.py +1 -1
hoho/wed.py
CHANGED
@@ -28,7 +28,17 @@ def preregister_mean_std(verts_to_transform, target_verts, single_scale=True):
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return transformed_verts
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def
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'''The function computes the Wireframe Edge Distance (WED) between two graphs.
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pd_vertices: list of predicted vertices
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pd_edges: list of predicted edges
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@@ -51,13 +61,9 @@ def compute_WED(pd_vertices, pd_edges, gt_vertices, gt_edges, cv=-1/4, ce=1.0, n
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if preregister:
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pd_vertices = preregister_mean_std(pd_vertices, gt_vertices, single_scale=single_scale)
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cv = -cv * diameter
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elif cv == 0:
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# Cost of adding or deleting a vertex is set to the average distance of the ground truth vertices from their mean
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cv = np.linalg.norm(np.mean(gt_vertices, axis=0) - gt_vertices, axis=1).mean()
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# Step 0: Prenormalize / preregister
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@@ -74,11 +80,11 @@ def compute_WED(pd_vertices, pd_edges, gt_vertices, gt_edges, cv=-1/4, ce=1.0, n
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# Additional: Vertex Deletion
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unmatched_pd_indices = set(range(len(pd_vertices))) - set(row_ind)
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deletion_costs =
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# Step 3: Vertex Insertion
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unmatched_gt_indices = set(range(len(gt_vertices))) - set(col_ind)
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insertion_costs =
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# Step 4: Edge Deletion and Insertion
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updated_pd_edges = [(col_ind[np.where(row_ind == edge[0])[0][0]], col_ind[np.where(row_ind == edge[1])[0][0]]) for edge in pd_edges if edge[0] in row_ind and edge[1] in row_ind]
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return transformed_verts
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+
def update_cv(cv, gt_vertices):
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if cv < 0:
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diameter = cdist(gt_vertices, gt_vertices).max()
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# Cost of adding or deleting a vertex is set to -cv times the diameter of the ground truth wireframe
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cv = -cv * diameter
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elif cv == 0:
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# Cost of adding or deleting a vertex is set to the average distance of the ground truth vertices from their mean
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cv = np.linalg.norm(np.mean(gt_vertices, axis=0) - gt_vertices, axis=1).mean()
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return cv
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def compute_WED(pd_vertices, pd_edges, gt_vertices, gt_edges, cv_ins=-1/2, cv_del=-1/4, ce=1.0, normalized=True, preregister=True, single_scale=True):
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'''The function computes the Wireframe Edge Distance (WED) between two graphs.
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pd_vertices: list of predicted vertices
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pd_edges: list of predicted edges
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if preregister:
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pd_vertices = preregister_mean_std(pd_vertices, gt_vertices, single_scale=single_scale)
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cv_del = update_cv(cv_del, gt_vertices)
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cv_ins = update_cv(cv_ins, gt_vertices)
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# Step 0: Prenormalize / preregister
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# Additional: Vertex Deletion
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unmatched_pd_indices = set(range(len(pd_vertices))) - set(row_ind)
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deletion_costs = cv_del * len(unmatched_pd_indices)
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# Step 3: Vertex Insertion
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unmatched_gt_indices = set(range(len(gt_vertices))) - set(col_ind)
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insertion_costs = cv_ins * len(unmatched_gt_indices)
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# Step 4: Edge Deletion and Insertion
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updated_pd_edges = [(col_ind[np.where(row_ind == edge[0])[0][0]], col_ind[np.where(row_ind == edge[1])[0][0]]) for edge in pd_edges if edge[0] in row_ind and edge[1] in row_ind]
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setup.py
CHANGED
@@ -6,7 +6,7 @@ with open('requirements.txt') as f:
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required = f.read().splitlines()
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setup(name='hoho',
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version='0.0.
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description='Tools and utilites for the HoHo Dataset and S23DR Competition',
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url='usm3d.github.io',
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author='Jack Langerman, Dmytro Mishkin, S23DR Orgainizing Team',
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required = f.read().splitlines()
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setup(name='hoho',
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version='0.0.4',
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description='Tools and utilites for the HoHo Dataset and S23DR Competition',
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url='usm3d.github.io',
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author='Jack Langerman, Dmytro Mishkin, S23DR Orgainizing Team',
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