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import argparse
import os
import os.path as osp
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import mmcv
import numpy as np
try:
import imageio
except ImportError:
imageio = None
def parse_args():
parser = argparse.ArgumentParser(description='Create GIF for demo')
parser.add_argument(
'image_dir',
help='directory where result '
'images save path generated by ‘analyze_results.py’')
parser.add_argument(
'--out',
type=str,
default='result.gif',
help='gif path where will be saved')
args = parser.parse_args()
return args
def _generate_batch_data(sampler, batch_size):
batch = []
for idx in sampler:
batch.append(idx)
if len(batch) == batch_size:
yield batch
batch = []
if len(batch) > 0:
yield batch
def create_gif(frames, gif_name, duration=2):
"""Create gif through imageio.
Args:
frames (list[ndarray]): Image frames
gif_name (str): Saved gif name
duration (int): Display interval (s),
Default: 2
"""
if imageio is None:
raise RuntimeError('imageio is not installed,'
'Please use “pip install imageio” to install')
imageio.mimsave(gif_name, frames, 'GIF', duration=duration)
def create_frame_by_matplotlib(image_dir,
nrows=1,
fig_size=(300, 300),
font_size=15):
"""Create gif frame image through matplotlib.
Args:
image_dir (str): Root directory of result images
nrows (int): Number of rows displayed, Default: 1
fig_size (tuple): Figure size of the pyplot figure.
Default: (300, 300)
font_size (int): Font size of texts. Default: 15
Returns:
list[ndarray]: image frames
"""
result_dir_names = os.listdir(image_dir)
assert len(result_dir_names) == 2
# Longer length has higher priority
result_dir_names.reverse()
images_list = []
for dir_names in result_dir_names:
images_list.append(mmcv.scandir(osp.join(image_dir, dir_names)))
frames = []
for paths in _generate_batch_data(zip(*images_list), nrows):
fig, axes = plt.subplots(nrows=nrows, ncols=2)
fig.suptitle('Good/bad case selected according '
'to the COCO mAP of the single image')
det_patch = mpatches.Patch(color='salmon', label='prediction')
gt_patch = mpatches.Patch(color='royalblue', label='ground truth')
# bbox_to_anchor may need to be finetuned
plt.legend(
handles=[det_patch, gt_patch],
bbox_to_anchor=(1, -0.18),
loc='lower right',
borderaxespad=0.)
if nrows == 1:
axes = [axes]
dpi = fig.get_dpi()
# set fig size and margin
fig.set_size_inches(
(fig_size[0] * 2 + fig_size[0] // 20) / dpi,
(fig_size[1] * nrows + fig_size[1] // 3) / dpi,
)
fig.tight_layout()
# set subplot margin
plt.subplots_adjust(
hspace=.05,
wspace=0.05,
left=0.02,
right=0.98,
bottom=0.02,
top=0.98)
for i, (path_tuple, ax_tuple) in enumerate(zip(paths, axes)):
image_path_left = osp.join(
osp.join(image_dir, result_dir_names[0], path_tuple[0]))
image_path_right = osp.join(
osp.join(image_dir, result_dir_names[1], path_tuple[1]))
image_left = mmcv.imread(image_path_left)
image_left = mmcv.rgb2bgr(image_left)
image_right = mmcv.imread(image_path_right)
image_right = mmcv.rgb2bgr(image_right)
if i == 0:
ax_tuple[0].set_title(
result_dir_names[0], fontdict={'size': font_size})
ax_tuple[1].set_title(
result_dir_names[1], fontdict={'size': font_size})
ax_tuple[0].imshow(
image_left, extent=(0, *fig_size, 0), interpolation='bilinear')
ax_tuple[0].axis('off')
ax_tuple[1].imshow(
image_right,
extent=(0, *fig_size, 0),
interpolation='bilinear')
ax_tuple[1].axis('off')
canvas = fig.canvas
s, (width, height) = canvas.print_to_buffer()
buffer = np.frombuffer(s, dtype='uint8')
img_rgba = buffer.reshape(height, width, 4)
rgb, alpha = np.split(img_rgba, [3], axis=2)
img = rgb.astype('uint8')
frames.append(img)
return frames
def main():
args = parse_args()
frames = create_frame_by_matplotlib(args.image_dir)
create_gif(frames, args.out)
if __name__ == '__main__':
main()
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