Esempio n. 1
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    def verify_upscaling_works(self) -> None:
        """
        Verify the upscaler works by upscaling a very small frame, and throws a descriptive error if it doesn't.
        """
        test_file = self.context.workspace + "test_frame.jpg"
        test_file_upscaled = self.context.workspace + "test_frame_upscaled.jpg"

        test_frame = Frame()
        test_frame.create_new(2, 2)
        test_frame.save_image(test_file)

        self.upscale_file(test_file, test_file_upscaled)

        if not file_exists(test_file_upscaled):
            print(
                "Your computer could not upscale a test image, which is required for dandere2x to work."
            )
            print(
                "This may be a hardware issue or a software issue - verify your computer is capable of upscaling "
                "images using the selected upscaler.")

            raise Exception("Your computer could not upscale the test file.")

        os.remove(test_file)
        os.remove(test_file_upscaled)
    def verify_upscaling_works(self) -> None:
        """
        Verify the upscaler works by upscaling a very small frame, and throws a descriptive error if it doesn't.
        """
        test_file = self.context.workspace + "test_frame.jpg"
        test_file_upscaled = self.context.workspace + "test_frame_upscaled.jpg"

        test_frame = Frame()
        test_frame.create_new(2, 2)
        test_frame.save_image(test_file)

        self.log.info(
            "Attempting to upscale file %s into %s to ensure waifu2x is working..."
            % (test_file, test_file_upscaled))

        self.upscale_file(test_file, test_file_upscaled)

        if not file_exists(test_file_upscaled):
            self.log.error(
                "Your computer could not upscale a test image, which is required for dandere2x to work."
            )
            self.log.error(
                "This may be a hardware issue or a software issue - verify your computer is capable of upscaling "
                "images using the selected upscaler.")

            raise Exception("Your computer could not upscale the test file.")

        self.log.info(
            "Upscaling *seems* successful. Deleting files and continuing forward. "
        )

        os.remove(test_file)
        os.remove(test_file_upscaled)
Esempio n. 3
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def debug_image(block_size, frame_base, list_predictive, list_differences,
                output_location):
    logger = logging.getLogger(__name__)

    difference_vectors = []
    predictive_vectors = []
    out_image = Frame()
    out_image.create_new(frame_base.width, frame_base.height)
    out_image.copy_image(frame_base)

    black_image = Frame()
    black_image.create_new(frame_base.width, frame_base.height)

    if not list_predictive and not list_differences:
        out_image.save_image(output_location)
        return

    if list_predictive and not list_differences:
        out_image.copy_image(frame_base)
        out_image.save_image(output_location)
        return

    # load list into vector displacements
    for x in range(int(len(list_differences) / 4)):
        difference_vectors.append(
            DisplacementVector(int(list_differences[x * 4]),
                               int(list_differences[x * 4 + 1]),
                               int(list_differences[x * 4 + 2]),
                               int(list_differences[x * 4 + 3])))
    for x in range(int(len(list_predictive) / 4)):
        if (int(list_predictive[x * 4 + 0]) != int(list_predictive[x * 4 + 1])) and \
                (int(list_predictive[x * 4 + 2]) != int(list_predictive[x * 4 + 3])):
            predictive_vectors.append(
                DisplacementVector(int(list_predictive[x * 4 + 0]),
                                   int(list_predictive[x * 4 + 1]),
                                   int(list_predictive[x * 4 + 2]),
                                   int(list_predictive[x * 4 + 3])))

    # copy over predictive vectors into new image
    for vector in difference_vectors:
        out_image.copy_block(black_image, block_size, vector.x_1, vector.y_1,
                             vector.x_1, vector.y_1)

    out_image.save_image_quality(output_location, 25)
Esempio n. 4
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    def run(self):
        self.log.info("Run called.")

        for x in range(self.start_frame, self.frame_count):

            # Stop if thread is killed
            if not self.context.controller.is_alive():
                break

            # Files needed to create a residual image
            f1 = Frame()
            f1.load_from_string_controller(
                self.input_frames_dir + "frame" + str(x + 1) +
                self.extension_type, self.context.controller)
            # Load the neccecary lists to compute this iteration of residual making
            residual_data = get_list_from_file_and_wait(
                self.residual_data_dir + "residual_" + str(x) + ".txt",
                self.context.controller)

            prediction_data = get_list_from_file_and_wait(
                self.pframe_data_dir + "pframe_" + str(x) + ".txt",
                self.context.controller)

            # stop if thread is killed
            if not self.context.controller.is_alive():
                break

            # Create the output files..
            debug_output_file = self.debug_dir + "debug" + str(
                x + 1) + self.extension_type
            output_file = self.residual_images_dir + "output_" + get_lexicon_value(
                6, x) + ".jpg"

            # Save to a temp folder so waifu2x-vulkan doesn't try reading it, then move it
            out_image = self.make_residual_image(self.context, 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.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(output_file, self.temp_image)

            # With this change the wrappers must be modified to not try deleting the non existing residual file
            if self.context.debug == 1:
                self.debug_image(self.block_size, f1, prediction_data,
                                 residual_data, debug_output_file)
Esempio n. 5
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    def debug_image(block_size, frame_base, list_predictive, list_differences,
                    output_location):
        """
        Note:
            I haven't made an effort to maintain this method, as it's only for debugging.

        This section can best be explained through pictures. A visual way of expressing what 'debug'
        is doing is this section in the wiki.

        https://github.com/aka-katto/dandere2x/wiki/How-Dandere2x-Works#part-1-identifying-what-needs-to-be-drawn

        In other words, this method shows where residuals are, and is useful for finding good settings to use for a video.

        Inputs:
            - frame(x)
            - Residual vectors mapping frame(x)_residual -> frame(x)

        Output:
            - frame(x) minus frame(x)_residuals = debug_image
        """
        logger = logging.getLogger(__name__)

        difference_vectors = []
        predictive_vectors = []
        out_image = Frame()
        out_image.create_new(frame_base.width, frame_base.height)
        out_image.copy_image(frame_base)

        black_image = Frame()
        black_image.create_new(frame_base.width, frame_base.height)

        if not list_predictive and not list_differences:
            out_image.save_image(output_location)
            return

        if list_predictive and not list_differences:
            out_image.copy_image(frame_base)
            out_image.save_image(output_location)
            return

        # load list into vector displacements
        for x in range(int(len(list_differences) / 4)):
            difference_vectors.append(
                DisplacementVector(int(list_differences[x * 4]),
                                   int(list_differences[x * 4 + 1]),
                                   int(list_differences[x * 4 + 2]),
                                   int(list_differences[x * 4 + 3])))
        for x in range(int(len(list_predictive) / 4)):
            if (int(list_predictive[x * 4 + 0]) != int(list_predictive[x * 4 + 1])) and \
                    (int(list_predictive[x * 4 + 2]) != int(list_predictive[x * 4 + 3])):
                predictive_vectors.append(
                    DisplacementVector(int(list_predictive[x * 4 + 0]),
                                       int(list_predictive[x * 4 + 1]),
                                       int(list_predictive[x * 4 + 2]),
                                       int(list_predictive[x * 4 + 3])))

        # copy over predictive vectors into new image
        for vector in difference_vectors:
            out_image.copy_block(black_image, block_size, vector.x_1,
                                 vector.y_1, vector.x_1, vector.y_1)

        out_image.save_image_quality(output_location, 25)
Esempio n. 6
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def residual_loop(context):
    """
    Call the 'make_residual_image' method for every image that needs to be made into a residual.

    Method Tasks:
        - Load and wait for the files needed to create a residual image.
        - Call 'make_residual_image' once the needed files exist
    """

    # load variables from context
    workspace = context.workspace
    residual_upscaled_dir = context.residual_upscaled_dir
    residual_images_dir = context.residual_images_dir
    residual_data_dir = context.residual_data_dir
    pframe_data_dir = context.pframe_data_dir
    input_frames_dir = context.input_frames_dir
    frame_count = context.frame_count
    block_size = context.block_size
    extension_type = context.extension_type
    debug_dir = context.debug_dir
    debug = context.debug

    temp_image = context.temp_image_folder + "tempimage.jpg"

    logger = logging.getLogger(__name__)
    logger.info((workspace, 1, frame_count, block_size))

    # for every frame in the video, create a residual_frame given the text files.
    for x in range(1, frame_count):
        f1 = Frame()
        f1.load_from_string_wait(input_frames_dir + "frame" + str(x + 1) +
                                 extension_type)

        # Load the neccecary lists to compute this iteration of residual making
        residual_data = get_list_from_file(residual_data_dir + "residual_" +
                                           str(x) + ".txt")
        prediction_data = get_list_from_file(pframe_data_dir + "pframe_" +
                                             str(x) + ".txt")

        # Create the output files..
        debug_output_file = debug_dir + "debug" + str(x + 1) + extension_type
        output_file = residual_images_dir + "output_" + get_lexicon_value(
            6, x) + ".jpg"

        # Save to a temp folder so waifu2x-vulkan doesn't try reading it, then move it
        out_image = make_residual_image(context, 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 = 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(output_file, temp_image)

        # With this change the wrappers must be modified to not try deleting the non existing residual file

        if debug == 1:
            debug_image(block_size, f1, prediction_data, residual_data,
                        debug_output_file)