From 64c36c2b3aab8ff4ba3e1da8d1b9523fa9e08b68 Mon Sep 17 00:00:00 2001 From: xiuming Date: Fri, 28 May 2021 22:55:56 -0400 Subject: [PATCH] add make_comparison_video --- xiuminglib/vis/video.py | 118 ++++++++++++++++++++++++++++++++++++++-- 1 file changed, 114 insertions(+), 4 deletions(-) diff --git a/xiuminglib/vis/video.py b/xiuminglib/vis/video.py index 8df2260..73b067a 100644 --- a/xiuminglib/vis/video.py +++ b/xiuminglib/vis/video.py @@ -1,13 +1,14 @@ from os.path import join, dirname import numpy as np -from ..log import get_logger -logger = get_logger() - +from .text import put_text from .. import const from ..os import makedirs from ..imprt import preset_import +from ..log import get_logger +logger = get_logger() + def make_video( imgs, fps=24, outpath=None, method='matplotlib', dpi=96, bitrate=-1): @@ -107,4 +108,113 @@ def img_plt(arr): else: raise ValueError(method) - logger.info("Images written as a video to:\n%s", outpath) + logger.debug("Images written as a video to:\n%s", outpath) + + +def make_comparison_video( + imgs1, imgs2, bar_width=4, bar_color=(1, 0, 0), sweep_vertically=False, + sweeps=1, label1='', label2='', font_size=None, font_ttf=None, + label1_top_left_xy=None, label2_top_left_xy=None, **make_video_kwargs): + """Writes two lists of images into a comparison video that toggles between + two videos with a sweeping bar. + + Args: + imgs? (list(numpy.ndarray)): Each image should be of type ``uint8`` or + ``uint16`` and of shape H-by-W (grayscale) or H-by-W-by-3 (RGB). + bar_width (int, optional): Width of the sweeping bar. + bar_color (tuple(float), optional): Bar and label RGB, normalized to + :math:`[0,1]`. Defaults to red. + sweep_vertically (bool, optional): Whether to sweep vertically or + horizontally. + sweeps (int, optional): Number of sweeps. + label? (str, optional): Label for each video. + font_size (int, optional): Font size. + font_ttf (str, optional): Path to the .ttf font file. Defaults to Arial. + label?_top_left_xy (tuple(int), optional): The XY coordinate of the + label's top left corner. + make_video_kwargs (dict, optional): Keyword arguments for + :func:`make_video`. + + Writes + - A comparison video. + """ + # Bar is perpendicular to sweep-along + sweep_along = 0 if sweep_vertically else 1 + bar_along = 1 if sweep_vertically else 0 + + # Number of frames + n_frames = len(imgs1) + assert n_frames == len(imgs2), \ + "Videos to be compared have different numbers of frames" + + img_shape = imgs1[0].shape + + # Bar color according to image dtype + img_dtype = imgs1[0].dtype + bar_color = np.array(bar_color, dtype=img_dtype) + if np.issubdtype(img_dtype, np.integer): + bar_color *= np.iinfo(img_dtype).max + + # Map from frame index to bar location, considering possibly multiple trips + bar_locs = [] + for i in range(sweeps): + ind = np.arange(0, img_shape[sweep_along]) + if i % 2 == 1: # reverse every other trip + ind = ind[::-1] + bar_locs.append(ind) + bar_locs = np.hstack(bar_locs) # all possible locations + ind = np.linspace(0, len(bar_locs) - 1, num=n_frames, endpoint=True) + bar_locs = [bar_locs[int(x)] for x in ind] # uniformly sampled + + # Label locations + if label1_top_left_xy is None: + # Label 1 at top left corner + label1_top_left_xy = (int(0.1 * img_shape[1]), int(0.05 * img_shape[0])) + if label2_top_left_xy is None: + if sweep_vertically: + # Label 2 at bottom left corner + label2_top_left_xy = ( + int(0.1 * img_shape[1]), int(0.75 * img_shape[0])) + else: + # Label 2 at top right corner + label2_top_left_xy = ( + int(0.7 * img_shape[1]), int(0.05 * img_shape[0])) + + frames = [] + for i, (img1, img2) in enumerate(zip(imgs1, imgs2)): + assert img1.shape == img_shape, f"`imgs1[{i}]` has a differnet shape" + assert img2.shape == img_shape, f"`imgs2[{i}]` has a differnet shape" + assert img1.dtype == img_dtype, f"`imgs1[{i}]` has a differnet dtype" + assert img2.dtype == img_dtype, f"`imgs2[{i}]` has a differnet dtype" + + # Label the two images + img1 = put_text( + img1, label1, label_top_left_xy=label1_top_left_xy, + font_size=font_size, font_color=bar_color, font_ttf=font_ttf) + img2 = put_text( + img2, label2, label_top_left_xy=label2_top_left_xy, + font_size=font_size, font_color=bar_color, font_ttf=font_ttf) + + # Bar start and end + bar_loc = bar_locs[i] + bar_width_half = bar_width // 2 + bar_start = max(0, bar_loc - bar_width_half) + bar_end = min(bar_loc + bar_width_half, img_shape[sweep_along]) + + # Up to bar start, we show Image 1; bar end onwards, Image 2 + img1 = np.take(img1, range(bar_start), axis=sweep_along) + img2 = np.take( + img2, range(bar_end, img_shape[sweep_along]), axis=sweep_along) + + # Between the two images, we show the bar + actual_bar_width = img_shape[ + sweep_along] - img1.shape[sweep_along] - img2.shape[sweep_along] + reps = [1, 1, 1] + reps[sweep_along] = actual_bar_width + reps[bar_along] = img_shape[bar_along] + bar_img = np.tile(bar_color, reps) + + frame = np.concatenate((img1, bar_img, img2), axis=sweep_along) + frames.append(frame) + + make_video(frames, **make_video_kwargs)