def regularize_coarse(lenses, coarse_costs, disparities, penalty1=0.08, penalty2=0.15, max_cost=10.0):
intensity_grid = dict()
tmp_costs = dict()
coarse_disp = dict()
for lcoord in lenses:
intensity_grid[lcoord] = np.mean(lenses[lcoord].img[lenses[lcoord].mask > 0])
sgm_cost = rtxsgm.hex_sgm(coarse_costs, intensity_grid, penalty1, penalty2, max_cost=max_cost)
for lcoord in sgm_cost:
coarse_disp[lcoord], _ = rtxdisp.cost_minimum_interp(sgm_cost[lcoord], disparities)
return coarse_disp
def real_lut(lens,
lenses,
coarse_costs,
disparities,
max_cost=10.0,
nb_args=None):
# get some parameters
target_lenses = list(nb_args['target_lenses'].values())
min_disp = nb_args['min_disp']
max_disp = nb_args['max_disp']
trade_off = nb_args['trade_off']
# LUT to pick best combination or best performances
B = np.array([[np.sqrt(3) / 2, 0.5], [0, 1]]).T
#assert len(coarse_costs) <= len(target_lenses)
offsets = []
tref = rtxhexgrid.hex_focal_type(lens.lcoord)
#read the lut
lut_filename = '../disparity/lut_table.json'
with open(lut_filename, 'r') as f:
lut_str = json.load(f)
lut_length = len(lut_str['most_acc_0'])
lut_step = (max_disp - min_disp) / lut_length
mavg = 0
mvavg = 0
counter = 0
for i, ctmp in enumerate(coarse_costs):
m, mval = rtxdisp.cost_minimum_interp(ctmp, disparities)
mvavg += mval
mavg += m
counter += 1
# m avg should be the value for the disparity
mavg /= (counter)
mvavg /= counter
# look for the correct index
disp_int = lut_str['disp_int_interp']
disp_int['0'][0] = 20.0 #disparities[len(disparities)-1]
disp_int[str(len(disp_int) - 1)][1] = 0.0
disp_vals = lut_str['disp_vals_interp']
found = False
finished = False
jj = 0
while (not found and not finished):
if jj >= len(disp_int):
finished = True
jj = 0
elif mavg < disp_int[str(jj)][0] and mavg > disp_int[str(jj)][1]:
found = True
else:
jj += 1
### need to show somehow if I didn't find it
#if (finished and not found):
#print("Not found! \nmavg={0}\ndisp_int={1}\ndisp_vals={2}\n".format(mavg, disp_int, disp_vals))
index_lut = jj #lut_length - math.floor(m / (lut_step))
#print("m:{0}, mval:{1}, index:{2}".format(mavg, mvavg, jj))
if trade_off == 1:
if tref == 0:
strat = lut_str['most_acc_0'][index_lut]
elif tref == 1:
strat = lut_str['most_acc_1'][index_lut]
elif tref == 2:
strat = lut_str['most_acc_2'][index_lut]
elif trade_off == 0:
if tref == 0:
strat = lut_str['best_perf_0'][index_lut]
elif tref == 1:
strat = lut_str['best_perf_1'][index_lut]
elif tref == 2:
strat = lut_str['best_perf_2'][index_lut]
targets = from_strat_to_offsets(strat)
return targets, mavg