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Commit 3b6137be authored by Andrey Filippov's avatar Andrey Filippov
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Implemented 2-stage inference network to be used with TP in Java

parent bcf427de
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explore_data5.py
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infer_qcds_01.py 0 → 100644
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nn_ds_neibs18.py 0 → 100644
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nn_ds_neibs19.py 0 → 100644
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nn_ds_neibs20.py 0 → 100644
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nn_ds_neibs21.py 0 → 100644
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nn_eval_01.py
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......@@ -16,7 +16,7 @@ import sys
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import qcstereo_functions as qsf
#import xml.etree.ElementTree as ET
......@@ -53,8 +53,17 @@ TILE_SIDE, TILE_LAYERS, TWO_TRAINS, NET_ARCH1, NET_ARCH2 = [None]*5
ABSOLUTE_DISPARITY,SYM8_SUB, WLOSS_LAMBDA, SLOSS_LAMBDA, SLOSS_CLIP = [None]*5
SPREAD_CONVERGENCE, INTER_CONVERGENCE, HOR_FLIP, DISP_DIFF_CAP, DISP_DIFF_SLOPE = [None]*5
CLUSTER_RADIUS,ABSOLUTE_DISPARITY = [None]*2
FIGS_EXTENSIONS = ['png','pdf','svg']
#FIGS_ESXTENSIONS = ['png','pdf','svg']
EVAL_MODES = ["train","infer"]
FIGS_SAVESHOW = ['save','show']
globals().update(parameters)
try:
FIGS_EXTENSIONS = globals()['FIGS_ESXTENSIONS'] # fixing typo in configs
except:
pass
#exit(0)
......@@ -98,6 +107,7 @@ TIGHT_HPAD = 1.0
TIGHT_WPAD = 1.0
FIGSIZE = [8.5,11.0]
WOI_COLOR = "red"
TRANSPARENT = True # for export
#dbg_parameters
def get_fig_params(disparity_ranges):
......@@ -121,77 +131,133 @@ def get_fig_params(disparity_ranges):
fig_params = get_fig_params(dbg_parameters['disparity_ranges'])
pass
figs = []
def setlimsxy(lim_xy):
if not lim_xy is None:
plt.xlim(min(lim_xy[:2]),max(lim_xy[:2]))
plt.ylim(max(lim_xy[2:]),min(lim_xy[2:]))
for nfile, fpars in enumerate(fig_params):
if not fpars is None:
data = qsf.result_npy_prepare(files['result'][nfile], ABSOLUTE_DISPARITY, fix_nan=True, insert_deltas=True)
if not 'show' in FIGS_SAVESHOW:
plt.ioff()
for mode in ['train','infer']:
figs = []
ffiles = [] # no ext
def setlimsxy(lim_xy):
if not lim_xy is None:
plt.xlim(min(lim_xy[:2]),max(lim_xy[:2]))
plt.ylim(max(lim_xy[2:]),min(lim_xy[2:]))
for rng in fpars['ranges']:
lim_val = rng['lim_val']
lim_xy = rng['lim_xy']
fig = plt.figure(figsize=FIGSIZE)
fig.canvas.set_window_title(fpars['name'])
fig.suptitle(fpars['name'])
ax_conf=plt.subplot(322)
ax_conf.set_title("Ground truth confidence")
# fig.suptitle("Groud truth confidence")
plt.imshow(data[...,GT_CONF], vmin=0, vmax=CONF_MAX, cmap='gray')
if not lim_xy is None:
pass # show frame
xdata=[min(lim_xy[:2]),max(lim_xy[:2]),max(lim_xy[:2]),min(lim_xy[:2]),min(lim_xy[:2])]
ydata=[min(lim_xy[2:]),min(lim_xy[2:]),max(lim_xy[2:]),max(lim_xy[2:]),min(lim_xy[2:])]
plt.plot(xdata,ydata,color=WOI_COLOR)
for nfile, fpars in enumerate(fig_params):
if not fpars is None:
img_file = files['result'][nfile]
if mode == 'infer':
img_file = img_file.replace('.npy','-infer.npy')
try:
data,_ = qsf.result_npy_prepare(img_file, ABSOLUTE_DISPARITY, fix_nan=True, insert_deltas=True)
except:
print ("Image file does not exist:", img_file)
continue
# setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
for subindex, rng in enumerate(fpars['ranges']):
lim_val = rng['lim_val']
lim_xy = rng['lim_xy']
fig = plt.figure(figsize=FIGSIZE)
fig.canvas.set_window_title(fpars['name'])
fig.suptitle(fpars['name'])
ax_conf=plt.subplot(322)
ax_conf.set_title("Ground truth confidence")
# fig.suptitle("Groud truth confidence")
plt.imshow(data[...,GT_CONF], vmin=0, vmax=CONF_MAX, cmap='gray')
if not lim_xy is None:
pass # show frame
xdata=[min(lim_xy[:2]),max(lim_xy[:2]),max(lim_xy[:2]),min(lim_xy[:2]),min(lim_xy[:2])]
ydata=[min(lim_xy[2:]),min(lim_xy[2:]),max(lim_xy[2:]),max(lim_xy[2:]),min(lim_xy[2:])]
plt.plot(xdata,ydata,color=WOI_COLOR)
# setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_gtd=plt.subplot(321)
ax_gtd.set_title("Ground truth disparity map")
plt.imshow(data[...,GT_DISP], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_hed=plt.subplot(323)
ax_hed.set_title("Heuristic disparity map")
plt.imshow(data[...,HEUR_NAN], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_gtd=plt.subplot(321)
ax_gtd.set_title("Ground truth disparity map")
plt.imshow(data[...,GT_DISP], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_nnd=plt.subplot(325)
ax_nnd.set_title("Network disparity output")
plt.imshow(data[...,NN_NAN], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_hee=plt.subplot(324)
ax_hee.set_title("Heuristic disparity error")
plt.imshow(data[...,HEUR_DIFF], vmin=-ERR_AMPL, vmax=ERR_AMPL)
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_nne=plt.subplot(326)
ax_nne.set_title("Network disparity error")
plt.imshow(data[...,NN_DIFF], vmin=-ERR_AMPL, vmax=ERR_AMPL)
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_hed=plt.subplot(323)
ax_hed.set_title("Heuristic disparity map")
plt.imshow(data[...,HEUR_NAN], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_nnd=plt.subplot(325)
ax_nnd.set_title("Network disparity output")
plt.imshow(data[...,NN_NAN], vmin=lim_val[0], vmax=lim_val[1])
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_hee=plt.subplot(324)
ax_hee.set_title("Heuristic disparity error")
plt.imshow(data[...,HEUR_DIFF], vmin=-ERR_AMPL, vmax=ERR_AMPL)
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
ax_nne=plt.subplot(326)
ax_nne.set_title("Network disparity error")
plt.imshow(data[...,NN_DIFF], vmin=-ERR_AMPL, vmax=ERR_AMPL)
setlimsxy(lim_xy)
plt.colorbar(orientation='vertical') # location='bottom')
plt.tight_layout(rect =[0,0,1,TIGHT_TOP], h_pad = TIGHT_HPAD, w_pad = TIGHT_WPAD)
figs.append(fig)
fb_noext = os.path.splitext(os.path.basename(img_file))[0]#
if subindex > 0:
if subindex < 10:
fb_noext+="abcdefghi"[subindex-1]
else:
fb_noext+="-"+str(subindex)
ffiles.append(fb_noext)
pass
#whow to allow adjustment before applying tight_layout?
pass
for fig in figs:
fig.tight_layout(rect =[0,0,1,TIGHT_TOP], h_pad = TIGHT_HPAD, w_pad = TIGHT_WPAD)
if FIGS_EXTENSIONS and figs and 'save' in FIGS_SAVESHOW:
try:
print ("Creating output directory for figures: ",dirs['figures'])
os.makedirs(dirs['figures'])
except:
pass
pp=None
if 'pdf' in FIGS_EXTENSIONS:
if mode == 'infer':
pdf_path = os.path.join(dirs['figures'],"figures-infer.pdf")
else:
pdf_path = os.path.join(dirs['figures'],"figures-train.pdf")
pp= PdfPages(pdf_path)
plt.tight_layout(rect =[0,0,1,TIGHT_TOP], h_pad = TIGHT_HPAD, w_pad = TIGHT_WPAD)
for fb_noext, fig in zip(ffiles,figs):
for ext in FIGS_EXTENSIONS:
if ext == 'pdf':
pass
fig.savefig(pp,format='pdf')
else:
if mode == 'infer':
noext = fb_noext+'-infer'
else:
noext = fb_noext+'-train'
fig.savefig(
fname = os.path.join(dirs['figures'],noext+"."+ext),
transparent = TRANSPARENT,
)
pass
if pp:
pp.close()
figs.append(fig)
pass
#whow to allow adjustment before applying tight_layout?
pass
for fig in figs:
fig.tight_layout(rect =[0,0,1,TIGHT_TOP], h_pad = TIGHT_HPAD, w_pad = TIGHT_WPAD)
plt.show()
if 'show' in FIGS_SAVESHOW:
plt.show()
#FIGS_ESXTENSIONS
#qsf.evaluateAllResults(result_files = files['result'],
# absolute_disparity = ABSOLUTE_DISPARITY,
......
qcstereo_conf_sample.xml
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qcstereo_functions.py
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qcstereo_network.py
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......@@ -8,6 +8,21 @@ __email__ = "andrey@elphel.com"
import tensorflow as tf
import tensorflow.contrib.slim as slim
NN_LAYOUTS = {0:[0, 0, 0, 32, 20, 16],
1:[0, 0, 0, 256, 128, 64],
2:[0, 128, 32, 32, 32, 16],
3:[0, 0, 40, 32, 20, 16],
4:[0, 0, 0, 0, 16, 16],
5:[0, 0, 64, 32, 32, 16],
6:[0, 0, 32, 16, 16, 16],
7:[0, 0, 64, 16, 16, 16],
8:[0, 0, 0, 64, 20, 16],
9:[0, 0, 256, 64, 32, 16],
10:[0, 256, 128, 64, 32, 16],
11:[0, 0, 0, 0, 64, 32],
12:[0, 0, 256, 128, 64, 32],
13:[0, 0, 0, 256, 128, 32],
}
def lrelu(x):
return tf.maximum(x*0.2,x)
......
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