generating result images for publication

nn_eval_01.py

+#!/usr/bin/env python3
+
+__copyright__ = "Copyright 2018, Elphel, Inc."
+__license__   = "GPL-3.0+"
+__email__     = "andrey@elphel.com"
+
+
+from PIL import Image
+
+import os
+import sys
+import glob
+
+import numpy as np
+
+import time
+
+import matplotlib.pyplot as plt
+
+import qcstereo_functions as qsf
+
+#import xml.etree.ElementTree as ET
+
+qsf.TIME_START = time.time()
+qsf.TIME_LAST  = qsf.TIME_START
+
+IMG_WIDTH =        324 # tiles per image row
+DEBUG_LEVEL= 1
+
+try:
+    conf_file =  sys.argv[1]
+except IndexError:
+    print("Configuration path is required as a first argument. Optional second argument specifies root directory for data files")
+    exit(1)
+try:
+    root_dir =  sys.argv[2]
+except IndexError:
+    root_dir =  os.path.dirname(conf_file)
+    
+print ("Configuration file: " + conf_file)
+parameters, dirs, files, dbg_parameters = qsf.parseXmlConfig(conf_file, root_dir)
+"""
+Temporarily for backward compatibility
+"""
+if not "SLOSS_CLIP" in parameters:
+    parameters['SLOSS_CLIP'] = 0.5
+    print ("Old config, setting SLOSS_CLIP=", parameters['SLOSS_CLIP'])
+    
+"""
+Defined in config file
+"""
+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
+    
+globals().update(parameters)
+
+
+#exit(0)
+
+
+TILE_SIZE =         TILE_SIDE* TILE_SIDE # == 81
+FEATURES_PER_TILE =  TILE_LAYERS * TILE_SIZE# == 324
+BATCH_SIZE =       ([1,2][TWO_TRAINS])*2*1000//25 # == 80 Each batch of tiles has balanced D/S tiles, shuffled batches but not inside batches
+
+SUFFIX=(str(NET_ARCH1)+'-'+str(NET_ARCH2)+
+       (["R","A"][ABSOLUTE_DISPARITY]) +
+       (["NS","S8"][SYM8_SUB])+
+       "WLAM"+str(WLOSS_LAMBDA)+
+       "SLAM"+str(SLOSS_LAMBDA)+
+       "SCLP"+str(SLOSS_CLIP)+
+       (['_nG','_G'][SPREAD_CONVERGENCE])+
+       (['_nI','_I'][INTER_CONVERGENCE]) +
+       (['_nHF',"_HF"][HOR_FLIP]) +
+       ('_CP'+str(DISP_DIFF_CAP)) +
+       ('_S'+str(DISP_DIFF_SLOPE))
+       )
+
+##############################################################################
+cluster_size = (2 * CLUSTER_RADIUS + 1) * (2 * CLUSTER_RADIUS + 1)
+center_tile_index = 2 * CLUSTER_RADIUS * (CLUSTER_RADIUS + 1)
+qsf.prepareFiles(dirs, files, suffix = SUFFIX)
+
+#import tensorflow.contrib.slim as slim
+NN_DISP =   0
+HEUR_DISP = 1
+GT_DISP =   2
+GT_CONF =   3
+NN_NAN =    4
+HEUR_NAN =  5
+NN_DIFF =   6
+HEUR_DIFF = 7
+CONF_MAX = 0.7
+ERR_AMPL = 0.3
+TIGHT_TOP = 0.95
+TIGHT_HPAD = 1.0
+TIGHT_WPAD = 1.0
+FIGSIZE = [8.5,11.0]
+WOI_COLOR = "red"
+
+#dbg_parameters
+def get_fig_params(disparity_ranges):
+    fig_params = []
+    for dr in disparity_ranges:
+        if dr[-1][0]=='-':
+            fig_params.append(None)
+        else:
+            subs = []
+            for s in dr[:-1]:
+                mm = s[:2]
+                try:
+                    lims = s[2]
+                except IndexError:
+                    lims = None
+                subs.append({'lim_val':mm, 'lim_xy':lims})        
+            fig_params.append({'name':dr[-1],'ranges':subs}) 
+    return fig_params
+
+#try:
+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)
+        
+        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)
+            
+#            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_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)
+            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()
+
+
+
+#qsf.evaluateAllResults(result_files = files['result'],
+#                       absolute_disparity = ABSOLUTE_DISPARITY,
+#                       cluster_radius = CLUSTER_RADIUS)
+print("All done")
+exit (0)