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Bias relaxation toward source adjacency patterns

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This commit is contained in:
Meta Vens 2026-04-22 11:09:56 +01:00
commit f5ffab61a0
3 changed files with 89 additions and 0 deletions
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1
scripts/render_focus_crop.py
View file

@ -189,6 +189,7 @@ def _build_focus_states(
candidate_colors,
relax_base_energy,
anchor,
representative,
blend(anchor_delta_x, source_delta_x_t),
blend(anchor_delta_y, source_delta_y_t),
blend(anchor_delta_diag, source_delta_diag_t),

82
src/repixelizer/continuous.py
View file

@ -279,6 +279,16 @@ def _pairwise_candidate_energy(
return energy
def _reference_deltas(reference):
height = reference.shape[0]
width = reference.shape[1]
delta_x = reference[:, 1:, :] - reference[:, :-1, :] if width > 1 else None
delta_y = reference[1:, :, :] - reference[:-1, :, :] if height > 1 else None
delta_diag = reference[1:, 1:, :] - reference[:-1, :-1, :] if height > 1 and width > 1 else None
delta_anti = reference[1:, :-1, :] - reference[:-1, 1:, :] if height > 1 and width > 1 else None
return delta_x, delta_y, delta_diag, delta_anti
def _motif_candidate_energy(torch, candidate_colors, context_colors, anchor):
if candidate_colors.shape[0] < 2 or candidate_colors.shape[1] < 2:
return candidate_colors.new_zeros(candidate_colors.shape[:3])
@ -515,6 +525,7 @@ def _relax_candidate_selection(
candidate_colors,
base_energy,
anchor,
source_reference,
desired_delta_x,
desired_delta_y,
desired_delta_diag,
@ -534,6 +545,7 @@ def _relax_candidate_selection(
probs = (-base_energy / start_temp).softmax(dim=2)
loss_history: list[float] = []
final_energy = base_energy
source_delta_x, source_delta_y, source_delta_diag, source_delta_anti = _reference_deltas(source_reference)
for step in range(iterations):
context_colors = (candidate_colors * probs[..., None]).sum(dim=2)
@ -548,12 +560,30 @@ def _relax_candidate_selection(
orthogonal_weight=solver_params.relax_orthogonal_weight,
diagonal_weight=solver_params.relax_diagonal_weight,
)
if solver_params.relax_source_adjacency_weight > 0.0:
source_energy = _pairwise_candidate_energy(
candidate_colors,
context_colors,
source_delta_x,
source_delta_y,
source_delta_diag,
source_delta_anti,
orthogonal_weight=solver_params.relax_orthogonal_weight,
diagonal_weight=solver_params.relax_diagonal_weight,
)
final_energy = final_energy + source_energy * solver_params.relax_source_adjacency_weight
if solver_params.relax_motif_weight > 0.0:
motif_energy = _motif_candidate_energy(torch, candidate_colors, context_colors, anchor)
final_energy = final_energy + motif_energy * solver_params.relax_motif_weight
if solver_params.relax_source_motif_weight > 0.0:
source_motif_energy = _motif_candidate_energy(torch, candidate_colors, context_colors, source_reference)
final_energy = final_energy + source_motif_energy * solver_params.relax_source_motif_weight
if solver_params.relax_line_weight > 0.0:
line_energy = _line_candidate_energy(torch, candidate_colors, context_colors, anchor)
final_energy = final_energy + line_energy * solver_params.relax_line_weight
if solver_params.relax_source_line_weight > 0.0:
source_line_energy = _line_candidate_energy(torch, candidate_colors, context_colors, source_reference)
final_energy = final_energy + source_line_energy * solver_params.relax_source_line_weight
alpha = 1.0 if iterations <= 1 else step / float(iterations - 1)
temperature = start_temp + (end_temp - start_temp) * alpha
@ -579,6 +609,18 @@ def _relax_candidate_selection(
orthogonal_weight=solver_params.relax_orthogonal_weight,
diagonal_weight=solver_params.relax_diagonal_weight,
)
if solver_params.relax_source_adjacency_weight > 0.0:
handoff_source_energy = _pairwise_candidate_energy(
candidate_colors,
relaxed_context,
source_delta_x,
source_delta_y,
source_delta_diag,
source_delta_anti,
orthogonal_weight=solver_params.relax_orthogonal_weight,
diagonal_weight=solver_params.relax_diagonal_weight,
)
handoff_energy = handoff_energy + handoff_source_energy * solver_params.relax_source_adjacency_weight
if solver_params.relax_motif_weight > 0.0:
handoff_energy = handoff_energy + _motif_candidate_energy(
torch,
@ -586,6 +628,13 @@ def _relax_candidate_selection(
relaxed_context,
relaxed_context,
) * solver_params.relax_motif_weight
if solver_params.relax_source_motif_weight > 0.0:
handoff_energy = handoff_energy + _motif_candidate_energy(
torch,
candidate_colors,
relaxed_context,
source_reference,
) * solver_params.relax_source_motif_weight
if solver_params.relax_line_weight > 0.0:
handoff_energy = handoff_energy + _line_candidate_energy(
torch,
@ -593,6 +642,13 @@ def _relax_candidate_selection(
relaxed_context,
relaxed_context,
) * solver_params.relax_line_weight
if solver_params.relax_source_line_weight > 0.0:
handoff_energy = handoff_energy + _line_candidate_energy(
torch,
candidate_colors,
relaxed_context,
source_reference,
) * solver_params.relax_source_line_weight
selected = torch.argmin(handoff_energy, dim=2)
return selected, relaxed_context.detach(), loss_history
@ -792,12 +848,18 @@ def _structure_score(
anchor_adj = _adjacency_pattern_loss(candidate_t, anchor_t)
anchor_motif = _motif_pattern_loss(candidate_t, anchor_t)
anchor_line = _line_pattern_loss(torch, candidate_t, anchor_t)
source_adj = _adjacency_pattern_loss(candidate_t, representative_t)
source_motif = _motif_pattern_loss(candidate_t, representative_t)
source_line = _line_pattern_loss(torch, candidate_t, representative_t)
representative_match = (candidate_t - representative_t).abs().mean()
return (
boundary * solver_params.structure_boundary_weight
+ anchor_adj * solver_params.structure_anchor_adjacency_weight
+ anchor_motif * solver_params.structure_anchor_motif_weight
+ anchor_line * solver_params.structure_anchor_line_weight
+ source_adj * solver_params.structure_source_adjacency_weight
+ source_motif * solver_params.structure_source_motif_weight
+ source_line * solver_params.structure_source_line_weight
+ representative_match * solver_params.structure_representative_weight
)
@ -868,6 +930,7 @@ def _discrete_refine_output(
source_delta_y = source_delta_y_t[0] if source_delta_y_t is not None else None
source_delta_diag = source_delta_diag_t[0] if source_delta_diag_t is not None else None
source_delta_anti = source_delta_anti_t[0] if source_delta_anti_t is not None else None
source_ref_dx, source_ref_dy, source_ref_diag, source_ref_anti = _reference_deltas(representative)
def desired_delta(anchor_delta, source_delta):
if anchor_delta is None:
@ -890,6 +953,7 @@ def _discrete_refine_output(
candidate_colors,
relax_base_energy,
anchor,
representative,
desired_delta_x,
desired_delta_y,
desired_delta_diag,
@ -921,9 +985,27 @@ def _discrete_refine_output(
if solver_params.refine_motif_weight > 0.0:
motif_energy = _motif_candidate_energy(torch, candidate_colors, selected_colors, anchor)
energy = energy + motif_energy * solver_params.refine_motif_weight
if solver_params.structure_source_motif_weight > 0.0:
source_motif_energy = _motif_candidate_energy(torch, candidate_colors, selected_colors, representative)
energy = energy + source_motif_energy * solver_params.structure_source_motif_weight
if solver_params.refine_line_weight > 0.0:
line_energy = _line_candidate_energy(torch, candidate_colors, selected_colors, anchor)
energy = energy + line_energy * solver_params.refine_line_weight
if solver_params.structure_source_line_weight > 0.0:
source_line_energy = _line_candidate_energy(torch, candidate_colors, selected_colors, representative)
energy = energy + source_line_energy * solver_params.structure_source_line_weight
if solver_params.structure_source_adjacency_weight > 0.0:
source_adjacency_energy = _pairwise_candidate_energy(
candidate_colors,
selected_colors,
source_ref_dx,
source_ref_dy,
source_ref_diag,
source_ref_anti,
orthogonal_weight=solver_params.refine_orthogonal_weight,
diagonal_weight=solver_params.refine_diagonal_weight,
)
energy = energy + source_adjacency_energy * solver_params.structure_source_adjacency_weight
candidate_t = selected_colors[None, ...]
score = float(

6
src/repixelizer/params.py
View file

@ -31,13 +31,19 @@ class SolverHyperParams:
relax_anchor_scale: float = 0.50
relax_orthogonal_weight: float = 0.34
relax_diagonal_weight: float = 0.12
relax_source_adjacency_weight: float = 0.35
relax_motif_weight: float = 0.22
relax_line_weight: float = 0.06
relax_source_motif_weight: float = 0.30
relax_source_line_weight: float = 0.12
relax_handoff_weight: float = 0.18
structure_boundary_weight: float = 0.60
structure_anchor_adjacency_weight: float = 0.15
structure_anchor_motif_weight: float = 0.20
structure_anchor_line_weight: float = 0.10
structure_source_adjacency_weight: float = 0.35
structure_source_motif_weight: float = 0.40
structure_source_line_weight: float = 0.20
structure_representative_weight: float = 0.05
alpha_foreground_threshold: float = 0.50
alpha_representative_foreground_threshold: float = 0.60