Python imageio.mimsave方法代碼示例

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def create_gif(pgn, gif_path, duration):
    board_image = initial_board.copy()
    images = [array(board_image)]

    game = chess.ChessGame()
    moves = chess.get_moves_from_pgn(pgn)

    for move in moves:
        previous = game.state.copy()
        game.push(move)
        apply_move(board_image, game.state, previous)
        images.append(array(board_image))

    last = images[len(moves)]
    for i in range(3):
        images.append(last)

    imageio.mimsave(gif_path, images, duration=duration) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def save_movie(images, num_x, num_y, out_file=None, movie_id=0):
    if out_file is None:
        logger.warning('`out_file` not provided. Not saving.')
    else:
        images_ = []
        for i, image in enumerate(images):
            if _options['quantized']:
                image = dequantize(image)
            dim_c, dim_x, dim_y = image.shape[-3:]
            image = image.reshape((num_x, num_y, dim_c, dim_x, dim_y))
            image = image.transpose(0, 3, 1, 4, 2)
            image = image.reshape(num_x * dim_x, num_y * dim_y, dim_c)
            if _options['use_tanh']:
                image = 0.5 * (image + 1.)
            images_.append(image)
        imageio.mimsave(out_file, images_)

    visualizer.video(videofile=out_file, env=exp.NAME,
                     win='movie_{}'.format(movie_id)) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def train(self, data_loader, epochs, save_training_gif=True):
        if save_training_gif:
            # Fix latents to see how image generation improves during training
            fixed_latents = Variable(self.G.sample_latent(64))
            if self.use_cuda:
                fixed_latents = fixed_latents.cuda()
            training_progress_images = []

        for epoch in range(epochs):
            print("\nEpoch {}".format(epoch + 1))
            self._train_epoch(data_loader)

            if save_training_gif:
                # Generate batch of images and convert to grid
                img_grid = make_grid(self.G(fixed_latents).cpu().data)
                # Convert to numpy and transpose axes to fit imageio convention
                # i.e. (width, height, channels)
                img_grid = np.transpose(img_grid.numpy(), (1, 2, 0))
                # Add image grid to training progress
                training_progress_images.append(img_grid)

        if save_training_gif:
            imageio.mimsave('./training_{}_epochs.gif'.format(epochs),
                            training_progress_images) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def generate_gif(self, filenames, gif_filename):
        '''create an animated GIF given a list of images

        Args:
            filenames (list): list of image filenames, ordered in required sequence
            gif_filename (str): filepath of final GIF file

        Returns:
            nothing. Side effect is to save a GIF file at gif_filename

        '''
        images = []
        for filename in filenames:
            if os.path.exists(filename):
                logging.info("Adding to gif: image " + filename)
                images.append(imageio.imread(filename))

        logging.info("Creating GIF. This can take some time...")

        imageio.mimsave(gif_filename, images)

        logging.info("Gif generated at " + gif_filename) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def create_gif(scene, file_name, n_frames=60, size=(600, 600)):
    tdir = tempfile.gettempdir()
    window.record(scene, az_ang=360.0 / n_frames, n_frames=n_frames,
                  path_numbering=True, out_path=tdir + '/tgif',
                  size=size)

    angles = []
    for i in range(n_frames):
        if i < 10:
            angle_fname = f"tgif00000{i}.png"
        elif i < 100:
            angle_fname = f"tgif0000{i}.png"
        else:
            angle_fname = f"tgif000{i}.png"
        angles.append(io.imread(os.path.join(tdir, angle_fname)))

    io.mimsave(file_name, angles) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def save_video(frames, file, **kwargs):
    '''
    Save a series of drawings as a GIF or video.

    Arguments:
        frames: A list of `Drawing`s or a list of `numpy.array`s.
        file: File name or file like object to write the video to.  The
            extension determines the output format.
        align_bottom: If frames are different sizes, align the bottoms of each
            frame in the video.
        align_right: If frames are different sizes, align the right edge of each
            frame in the video.
        bg: If frames are different sizes, fill the background with this color.
            (default is white: (255, 255, 255, 255))
        duration: If writing a GIF, sets the duration of each frame.
        fps: If writing a video, sets the frame rate in FPS.
        **kwargs: Other arguments to imageio.mimsave().

    '''
    if isinstance(frames[0], Drawing):
        frames = render_svg_frames(frames, **kwargs)
    kwargs.pop('align_bottom', None)
    kwargs.pop('align_right', None)
    kwargs.pop('bg', None)
    imageio.mimsave(file, frames, **kwargs) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def animate(src, gif_name, reshape=None, fps=25):

    if not isinstance(src, list):

        if os.path.isdir(src):

            src = list(paths.list_images(src))

            for idx, image in enumerate(src):
                src[idx] = cv2.imread(image)

    if reshape:

        for idx, image in enumerate(src):
            src[idx] = cv2.resize(image, reshape)

    for idx, image in enumerate(src):
            src[idx] = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    src = np.array(src)
    
    imageio.mimsave(gif_name, src, fps=fps) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def test_save_imgs(self, faces_list, paths_list):
        for idx in range(len(paths_list[0])):
            src_name = os.path.splitext(os.path.basename(paths_list[0][idx]))[0]
            tar_name = os.path.splitext(os.path.basename(paths_list[1][idx]))[0]

            if self.opt.save_test_gif:
                import imageio
                imgs_numpy_list = []
                for face_idx in range(len(faces_list) - 1):  # remove target image
                    cur_numpy = np.array(self.visual.numpy2im(faces_list[face_idx][idx]))
                    imgs_numpy_list.extend([cur_numpy for _ in range(3)])
                saved_path = os.path.join(self.opt.results, "%s_%s.gif" % (src_name, tar_name))
                imageio.mimsave(saved_path, imgs_numpy_list)
            else:
                # concate src, inters, tar faces
                concate_img = np.array(self.visual.numpy2im(faces_list[0][idx]))
                for face_idx in range(1, len(faces_list)):
                    concate_img = np.concatenate((concate_img, np.array(self.visual.numpy2im(faces_list[face_idx][idx]))), axis=1)
                concate_img = Image.fromarray(concate_img)
                # save image
                saved_path = os.path.join(self.opt.results, "%s_%s.jpg" % (src_name, tar_name))
                concate_img.save(saved_path)

            print("[Success] Saved images to %s" % saved_path) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def make_movie_from_files(path='./data', name='', output='.'):
    """
    Visualization using numpy arrays (written via MPI I/O) and json description

    Produces one png file per time-step, combine as movie via e.g.
      > ffmpeg -i data/name_%08d.png name.mp4

    Args:
        path (str): path to data files
        name (str): name of the simulation (expects data to be in data path)
        output (str): path to output
    """

    img_files = sorted(glob.glob(f'{path}/{name}_*.png'))
    print(f'{path}{name}')

    images = []
    for fimg in img_files:
        img = imageio.imread(fimg)
        print(fimg, img.shape)
        images.append(imageio.imread(fimg))
    fname = f'{output}/{name}.mp4'
    imageio.mimsave(fname, images, fps=8) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def timer_tick(self):
        import imageio
        self.timer_count += 1

        if self.timer_count >= self.total_time_steps:
            self.iren.DestroyTimer()
            if self.gif_file is not None:
                assert len(self.gif_data) > 0
                imageio.mimsave(self.gif_file + '.gif', self.gif_data)
                import os
                for i in range(self.screenshot_count):
                    os.remove(self.gif_file + '%d.png' % i)
                return

        if self.gif_file is not None:
            if (self.timer_count % 60) == 0:
                self.screenshot(self.gif_file)
                path = self.gif_file + '%d.png' % (self.screenshot_count - 1)
                self.gif_data.append(imageio.imread(path)) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def to_movie(self, output_fn, fps=15., dpi=50, cut=None, cmap='gray', extension=1):
        viz = []
        with click.progressbar(self.mosaic_filenames, label="Reading mosaics", show_pos=True) as bar:
            for fn in bar:
                try:
                    frame = KeplerMosaicMovieFrame(fn)
                    fig = frame.to_fig(rowrange=self.rowrange, colrange=self.colrange,
                                       dpi=dpi, cut=cut, cmap=cmap, extension=extension,)
                    img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
                    img = img.reshape(fig.canvas.get_width_height()[::-1] + (3,))
                    pl.close(fig)  # Avoid memory leak!
                    viz.append(img)
                except InvalidFrameException:
                    print("InvalidFrameException for {}".format(fn))
                    # Save the output as a movie
        if output_fn.endswith('.gif'):
            kwargs = {'duration': 1. / fps}
        else:
            kwargs = {'fps': fps}
        imageio.mimsave(output_fn, viz, **kwargs) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def make_gif(self, epochs):
        """
        Make a gif from a multiple images of epochs
        :param epochs: num_epochs till now
        :return:
        """
        gen_image_plots = []
        for epoch in range(epochs + 1):
            img_epoch = '{}samples_epoch_{:d}.png'.format(self.config.out_dir, epoch)
            try:
                gen_image_plots.append(imageio.imread(img_epoch))
            except OSError as e:
                pass

        imageio.mimsave(self.config.out_dir + 'animation_epochs_{:d}.gif'.format(epochs), gen_image_plots, fps=2) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def dynamic_download_and_Synthesizing(illust_id, title=None, prefix=None):
    tag = 'Dynamic_Download_And_Synthesizing'
    d_json_data = 'https://www.pixiv.net/ajax/illust/' + str(illust_id) + '/ugoira_meta'
    d_json_decoded = json.loads(get_text_from_url(d_json_data))['body']
    src_zip_url = d_json_decoded['originalSrc']
    src_mime_type = d_json_decoded['mime_type']
    src_img_delay = int(d_json_decoded['frames'][0]['delay']) / 1000
    src_saved_path = save_path + 'TEMP' + global_symbol + str(illust_id) + global_symbol + \
                     src_zip_url.split('/')[-1]
    src_saved_dir = save_path + 'TEMP' + global_symbol + str(illust_id) + global_symbol
    src_final_dir = save_path + 'Dynamic' + global_symbol
    download_thread(src_zip_url, save_path, None, 'TEMP' + global_symbol + str(illust_id))
    while not os.path.exists(src_saved_path + '.done'):
        time.sleep(1)
        print_with_tag(tag, 'Waiting for complete...')
    print_with_tag(tag, ['Zip target downloaded:', src_saved_path])
    with zipfile.ZipFile(src_saved_path, 'r') as zip_file:
        zip_file.extractall(path=src_saved_dir)
    # get each frame
    sort_by_num = []
    frames = []
    for root, dirs, files in os.walk(src_saved_dir):
        for file in files:
            if file.endswith('jpg') or file.endswith('png'):
                sort_by_num.append(src_saved_dir + global_symbol + file)
    sort_by_num.sort()
    print_with_tag(tag, 'Reading each frame..')
    for each_frame in sort_by_num:
        frames.append(imageio.imread(each_frame))
    gif_save_dir = save_path + str(prefix) + global_symbol + year_month + str(
        day) + global_symbol + 'D-' + str(illust_id) + global_symbol
    gif_name_format = re.sub('[\/:*?"<>|]', '_', str(title)) + '-' + str(illust_id) + '.gif'
    if not os.path.exists(gif_save_dir):
        os.makedirs(gif_save_dir)
    print_with_tag(tag, 'Synthesizing dynamic images..')
    try:
        imageio.mimsave(gif_save_dir + gif_name_format, frames, duration=src_img_delay)
    except Exception as e:
        print_with_tag(tag, [gif_save_dir + gif_name_format])
        print_with_tag(tag, e)
        exit() 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def create_gif(self, dirname, density=False):
        images = []
        if density:
            filenames = [x for x in os.listdir(dirname) if '_density.png' in x]
            sorted_fnames = sorted(filenames, key=lambda x: int(x.split('_density.png')[0]))
        else:
            filenames = [x for x in os.listdir(dirname) if ('.png' in x and 'density' not in x)]
            sorted_fnames = sorted(filenames, key=lambda x: int(x.split('.png')[0]))
        for f in sorted_fnames:
            images.append(imageio.imread(os.path.join(dirname, f)))
        imageio.mimsave(os.path.join(dirname, 'exploration.gif'), images) 

# 需要導入模塊: import imageio [as 別名]
# 或者: from imageio import mimsave [as 別名]
def save(self, file_name):
        if self.enabled:
            path = os.path.join(self.dir_name, file_name)
            imageio.mimsave(path, self.frames, fps=self.fps)