Add the PSNR metrics computed directly by the encoder

metricsmanager.py

@@ -153,7 +153,12 @@ class profile:
 	def get_metrics_set(self, metric):
 		bitrates_list	= np.sum(self.dict['Bitrates'], axis = 0)
 		
-		if metric == 'mPSNR':
+		if metric == 'PSNR':
+			y_psnr			= np.array(self.dict['PSNR-Y'])
+			u_psnr			= np.array(self.dict['PSNR-U'])
+			v_psnr			= np.array(self.dict['PSNR-V'])
+		
+		elif metric == 'mPSNR':
 			y_psnr			= np.array(self.dict['mPSNRY'])
 			u_psnr			= np.array(self.dict['mPSNRU'])
 			v_psnr			= np.array(self.dict['mPSNRV'])
@@ -207,25 +212,26 @@ if __name__ == '__main__':
 		for metric in metrics:
 			x = []
 			y = []
-			for ratio in sorted(profiles1.keys()):
-				try:
+			try:
+				for ratio in sorted(profiles1.keys()):
 					metrics_set1 = profiles1[ratio].get_metrics_set(metric)
 					metrics_set2 = profiles2[ratio].get_metrics_set(metric)
-				except KeyError:
-					continue
-				x.append(ratio)
-				y.append(func(metrics_set1, metrics_set2))
-			plt.plot(x, y, label = metric)
+					x.append(ratio)
+					y.append(func(metrics_set1, metrics_set2))
+			except KeyError:
+				continue
+			else:
+				plt.plot(x, y, label = metric)
 
 		# Show
 		plt.title(title)
-		plt.xlabel(r'$\tau$')
+		plt.xlabel(r'$\tau = \frac{EL}{EL + BL}$')
 		plt.ylabel(ylabel)
 		plt.legend()
 		return fig
 	
 	# Main function
-	metrics = ['mPSNR', 'tPSNR', 'PSNR_DE0100', 'HDR-VQM']
+	metrics = ['PSNR', 'mPSNR', 'tPSNR', 'PSNR_DE0100', 'HDR-VQM']
 	
 	rate_figure = plot_bjontegaard(r'BD(SHM, HM) = $f(\tau)$',
 		scalables, simulcast,