smooth sequences

1 files changed, 31 insertions, 1 deletions

diff --git a/run.py b/run.py
index 397475f..6563b43 100644
--- a/run.py
+++ b/run.py
@@ -26,6 +26,7 @@ arguments_smooth = False
 arguments_aOffset = 0
 arguments_bOffset = 0
 arguments_mixVideos = False
+arguments_averageVideos = False
 
 for strOption, strArgument in getopt.getopt(sys.argv[1:], '', [ strParameter[2:] + '=' for strParameter in sys.argv[1::2] ])[0]:
 	print("{}: {}".format(strOption, strArgument))
@@ -49,6 +50,8 @@ for strOption, strArgument in getopt.getopt(sys.argv[1:], '', [ strParameter[2:]
 		arguments_smooth = bool(strArgument)
 	elif strOption == '--mix-videos':
 		arguments_mixVideos = bool(strArgument)
+	elif strOption == '--average-videos':
+		arguments_averageVideos = bool(strArgument)
 	elif strOption == '--a-offset':
 		arguments_aOffset = int(strArgument)
 	elif strOption == '--b-offset':
@@ -108,6 +111,26 @@ def process_two_videos(moduleNetwork, tensorOutput, a, b, a_offset, b_offset, st
 	steps *= dilate
 	return recurse_videos(moduleNetwork, tensorOutput, a, b, a_offset, b_offset, steps, steps, steps/2, dilate)
 
+def average_two_videos(moduleNetwork, tensorOutput, a, b, a_offset, b_offset, steps, dilate):
+	global index
+	index += 1
+	if (index % 10) == 0:
+		print("{}...".format(index))
+	frames = []
+	steps *= dilate
+	for i in range(0, steps * dilate, dilate):
+		a_fn = os.path.join(a, "frame_{:0>5}.png".format(int(frame_index + a_offset)))
+		b_fn = os.path.join(b, "frame_{:0>5}.png".format(int(frame_index + b_offset)))
+		print("{} => {}".format(a_fn, b_fn))
+		a_np = load_image(a_fn)
+		b_np = load_image(b_fn)
+		tensorInputFirst = torch.FloatTensor(a_np)
+		tensorInputSecond = torch.FloatTensor(b_np)
+		process(moduleNetwork, tensorInputFirst, tensorInputSecond, tensorOutput)
+		middle_np = tensorOutput.clamp(0.0, 1.0).numpy()
+		frames.append(middle_np)
+	return frames
+
 def process_tree(moduleNetwork, a, b, tensorOutput, steps, dilate):
 	global index
 	index += 1
@@ -201,7 +224,14 @@ elif arguments_mixVideos:
 	outputPath = './renders/' + arguments_strVideoOut
 	frames = process_two_videos(moduleNetwork, tensorOutput, arguments_strFirst, arguments_strSecond, arguments_aOffset, arguments_bOffset, arguments_steps, arguments_dilate)
 	frames = smooth_frames(moduleNetwork, tensorOutput, frames, arguments_smooth)
-	print("dilate... {}".format(arguments_dilate))
+	frames = dilate_frames(moduleNetwork, tensorOutput, frames, arguments_dilate)
+	store_frames(frames, outputPath)
+elif arguments_averageVideos:
+	print("average two videos...")
+	print("{} => {}".format(arguments_strFirst, arguments_strSecond))
+	outputPath = './renders/' + arguments_strVideoOut
+	frames = average_two_videos(moduleNetwork, tensorOutput, arguments_strFirst, arguments_strSecond, arguments_aOffset, arguments_bOffset, arguments_steps, arguments_dilate)
+	frames = smooth_frames(moduleNetwork, tensorOutput, frames, arguments_smooth)
 	frames = dilate_frames(moduleNetwork, tensorOutput, frames, arguments_dilate)
 	store_frames(frames, outputPath)
 elif arguments_steps == 0: