class AsyncFrameRead(threading.Thread):
"""
Read an image asynchronously
"""
def __init__(self, input_image: str, controller=Dandere2xController()):
# calling superclass init
threading.Thread.__init__(self, name="asyncframeread")
self.input_image = input_image
self.loaded_image = Frame()
self.load_complete = False
self.controller = controller
def run(self):
self.loaded_image.load_from_string_controller(self.input_image,
self.controller)
self.load_complete = True
def run(self):
self.log.info("Run called.")
for x in range(1, self.con.frame_count):
# Files needed to create a residual image
f1 = Frame()
f1.load_from_string_controller(self.con.input_frames_dir + "frame" + str(x + 1) + ".png",
self.controller)
# Load the neccecary lists to compute this iteration of residual making
residual_data = get_list_from_file_and_wait(self.con.residual_data_dir + "residual_" + str(x) + ".txt")
prediction_data = get_list_from_file_and_wait(self.con.pframe_data_dir + "pframe_" + str(x) + ".txt")
# Create the output files..
debug_output_file = self.con.debug_dir + "debug" + str(x + 1) + ".png"
output_file = self.con.residual_images_dir + "output_" + get_lexicon_value(6, x) + ".png"
# Save to a temp folder so waifu2x-vulkan doesn't try reading it, then move it
out_image = self.make_residual_image(self.con, f1, residual_data, prediction_data)
if out_image.get_res() == (1, 1):
"""
If out_image is (1,1) in size, then frame_x and frame_x+1 are identical.
We still need to save an outimage for sake of having N output images for N input images, so we
save these meaningless files anyways.
However, these 1x1 can slow whatever waifu2x implementation down, so we 'cheat' d2x
but 'fake' upscaling them, so that they don't need to be processed by waifu2x.
"""
# Location of the 'fake' upscaled image.
out_image = Frame()
out_image.create_new(2, 2)
output_file = self.con.residual_upscaled_dir + "output_" + get_lexicon_value(6, x) + ".png"
out_image.save_image(output_file)
else:
# This image has things to upscale, continue normally
out_image.save_image_temp(out_location=output_file, temp_location=self.con.temp_image)
# With this change the wrappers must be modified to not try deleting the non existing residual file
if self.con.debug is True:
self.debug_image(block_size=self.con.service_request.block_size, frame_base=f1,
list_predictive=prediction_data, list_residuals=residual_data,
output_location=debug_output_file)
def run(self):
self.log.info("Started")
self.pipe.start()
# Load the genesis image + the first upscaled image.
frame_previous = Frame()
frame_previous.load_from_string_controller(
self.context.merged_dir + "merged_" + str(1) + ".jpg",
self.controller)
# Load and pipe the 'first' image before we start the for loop procedure, since all the other images will
# inductively build off this first frame.
frame_previous = Frame()
frame_previous.load_from_string_controller(
self.context.merged_dir + "merged_" + str(1) + ".jpg",
self.controller)
self.pipe.save(frame_previous)
current_upscaled_residuals = Frame()
current_upscaled_residuals.load_from_string_controller(
self.context.residual_upscaled_dir + "output_" +
get_lexicon_value(6, 1) + ".png", self.controller)
last_frame = False
for x in range(1, self.context.frame_count):
########################################
# Pre-loop logic checks and conditions #
########################################
# Check if we're at the last image, which affects the behaviour of the loop.
if x == self.context.frame_count - 1:
last_frame = True
# Pre-load the next iteration of the loop image ahead of time, if we're not on the last frame.
if not last_frame:
"""
By asynchronously loading frames ahead of time, this provides a small but meaningful
boost in performance when spanned over N frames. There's some code over head but
it's well worth it.
"""
background_frame_load = AsyncFrameRead(
self.context.residual_upscaled_dir + "output_" +
get_lexicon_value(6, x + 1) + ".png", self.controller)
background_frame_load.start()
######################
# Core Logic of Loop #
######################
# Load the needed vectors to create the merged image.
prediction_data_list = get_list_from_file_and_wait(
self.context.pframe_data_dir + "pframe_" + str(x) + ".txt")
residual_data_list = get_list_from_file_and_wait(
self.context.residual_data_dir + "residual_" + str(x) + ".txt")
correction_data_list = get_list_from_file_and_wait(
self.context.correction_data_dir + "correction_" + str(x) +
".txt")
fade_data_list = get_list_from_file_and_wait(
self.context.fade_data_dir + "fade_" + str(x) + ".txt")
# Create the actual image itself.
current_frame = self.make_merge_image(
self.context, current_upscaled_residuals, frame_previous,
prediction_data_list, residual_data_list, correction_data_list,
fade_data_list)
###############
# Saving Area #
###############
# Directly write the image to the ffmpeg pipe line.
self.pipe.save(current_frame)
# Manually write the image if we're preserving frames (this is for enthusiasts / debugging).
# if self.preserve_frames:
# if True:
# output_file = self.context.merged_dir + "merged_" + str(x + 1) + ".jpg"
# background_frame_write = AsyncFrameWrite(current_frame, output_file)
# background_frame_write.start()
#######################################
# Assign variables for next iteration #
#######################################
if not last_frame:
# We need to wait until the next upscaled image exists before we move on.
while not background_frame_load.load_complete:
wait_on_file(self.context.residual_upscaled_dir +
"output_" + get_lexicon_value(6, x + 1) +
".png")
"""
Now that we're all done with the current frame, the current `current_frame` is now the frame_previous
(with respect to the next iteration). We could obviously manually load frame_previous = Frame(n-1) each
time, but this is an optimization that makes a substantial difference over N frames.
"""
frame_previous = current_frame
current_upscaled_residuals = background_frame_load.loaded_image
self.controller.update_frame_count(x)
self.pipe.kill()