Add analysis script

x265Intra_VS_Inter_analysis.py

+#!/usr/bin/env python3
+
+filename = 'out.txt'
+
+PredMode = {1:'inter', 2:'intra', 5:'skip'}
+CUData = {
+	'addr'    :int,
+	'depth'   :int,
+	'f_intra' :int,
+	'f_inter' :int,
+	'f_MVD'   :int,
+	'isLeaf'  :lambda x: bool(int(x)),
+	'predMode':lambda x: PredMode[int(x[0])]}
+
+# Parse data
+data = []
+import os
+with open(os.path.join(os.path.dirname(__file__), filename)) as f:
+	for line in f.readlines():
+		tokens = line.replace(':',' ').split()
+		cu = {k:CUData[k](v) for k, v in zip(tokens[0::2], tokens[1::2])}
+		data.append(cu)
+
+# Analyse
+count = dict(zip(PredMode.values(), [0]*len(PredMode)))
+errors = 0
+for cu in data:
+	addr     = cu['addr']
+	depth    = cu['depth']
+	isLeaf   = cu['isLeaf']
+	predMode = cu['predMode']
+	
+	count[predMode] += 1
+	
+	if isLeaf and depth > 0 and predMode != 'skip':
+		f_intra  = cu['f_intra']
+		f_inter  = cu['f_inter']
+		f_MVD    = cu['f_MVD']
+		df_ratio = (f_intra - f_inter) / max(f_intra, f_inter)
+		
+		if (predMode == 'intra' and df_ratio > 0) or (predMode == 'inter' and df_ratio < 0):
+			print('df_ratio: {:6.2f}\tf_MVD: {:6}\tpredMode: {}'.format(df_ratio, f_MVD, predMode))
+			errors += 1
+
+print('errors: {} ({:.0f})%'.format(errors, 100*errors/(count['intra'] + count['inter'])))
+print(count)
+