def preset_color_epe(kwargs):
# Flow directories
flo_est_dir = get_arg(kwargs, 'flo_dir',
lambda: ask_string(
'Estimated flow files directory ({s}): ', default='flo_est', is_path=True))
flo_gt_dir = get_arg(kwargs, 'flo_gt_dir',
lambda: ask_string(
'Ground truth flow files directory ({s}): ', default='flo_gt', is_path=True))
# Flow normalization
norm_type = get_arg(kwargs, 'norm_type',
lambda: ask_multichoice('EPE normalization type ({s}): ',
answer_map={'video': 'video', 'frame': 'frame', 'none': None}, default='frame'))
if norm_type == 'video':
clamp_pct = get_arg(kwargs, 'norm_clamp',
lambda: float(ask_string(
'Normalization clamp percentage ({s}): ', default='1.0')))
gamma = get_arg(kwargs, 'norm_gamma',
lambda: float(ask_string(
'Normalization gamma curve exponent ({s}): ', default='1.0')))
# Output options
out_figure, out_options = ask_video_or_figure(
kwargs, 'output_color_epe.mp4')
# Generate EPE data
flo_est = fv.input.flo(flo_est_dir)
flo_gt = fv.input.flo(flo_gt_dir)
epe_data = fv.endpoint_error(flo_est, flo_gt)
# Normalize EPE data and convert to image
if norm_type == 'frame':
epe_data = fv.normalize_frame(epe_data)
elif norm_type == 'video':
epe_data = fv.normalize_video(
epe_data, clamp_pct=clamp_pct, gamma=gamma, verbose=True)
image_data = fv.epe_to_rgb(epe_data, color=[255, 255, 255])
# Generate output
if out_figure:
(framerate) = out_options
out = fv.output.show_plot(
title='color_epe result', framerate=framerate)
out.show_all(image_data, show_count=True)
else:
(framerate, out_name) = out_options
out = fv.output.video(out_name, framerate=framerate)
out.add_all(image_data, verbose=True)
def preset_color_flow(kwargs):
# Flow files
flo_dir = get_arg(kwargs, 'flo_dir',
lambda: ask_string('Flow files directory ({s}): ', default='flo', is_path=True))
# Flow normalization
norm_type = get_arg(kwargs, 'norm_type',
lambda: ask_multichoice('Vector normalization type ({s}): ',
answer_map={'video': 'video', 'frame': 'frame', 'none': 'none'}, default='frame'))
if norm_type == 'video':
clamp_pct = get_arg(kwargs, 'norm_clamp', lambda: float(ask_string(
'Normalization clamp percentage ({s}): ', default='1.0')))
gamma = get_arg(kwargs, 'norm_gamma', lambda: float(ask_string(
'Normalization gamma curve exponent ({s}): ', default='1.0')))
# Output options
out_figure, out_options = ask_video_or_figure(
kwargs, 'output_color_flow.mp4')
# Read flow data and normalize
flo_data = fv.input.flo(flo_dir)
if norm_type == 'frame':
flo_data = fv.normalize_frame(flo_data)
elif norm_type == 'video':
flo_data = fv.normalize_video(
flo_data, clamp_pct=clamp_pct, gamma=gamma, verbose=True)
rgb_data = fv.flow_to_rgb(flo_data)
# Generate output
if out_figure:
(framerate) = out_options
out = fv.output.show_plot(
title='color_flow result', framerate=framerate)
out.show_all(rgb_data, show_count=True)
else:
(framerate, out_name) = out_options
out = fv.output.video(out_name, framerate=framerate)
out.add_all(rgb_data, verbose=True)
def preset_flow_arrows(kwargs):
# Flow files and RGB frames of video
flo_dir = get_arg(
kwargs, 'flo_dir', lambda: ask_string(
'Flow files directory ({s}): ', default='flo', is_path=True))
# Background settings
use_flow = get_arg(
kwargs, 'use_flow_colors',
lambda: ask_multichoice('Use flow colors for image? ({s}): ',
answer_map={
'y': True,
'n': False
},
default='n'))
if use_flow:
arrow_color = (0, 0, 0)
else:
arrow_color = 'flow'
rgb_dir = get_arg(
kwargs, 'image_dir', lambda: ask_string(
'Image directory ({s}): ', default='png', is_path=True))
# Arrow subsampling
subsample_ratio = get_arg(
kwargs, 'subsample_ratio', lambda: float(
ask_string('Flow subsample ratio ({s}): ', default='16.0')))
# Output options
out_figure, out_options = ask_video_or_figure(kwargs,
'output_flow_arrows.mp4')
# Add points and generate image
flo_data = fv.input.flo(flo_dir)
if use_flow:
flo_data_norm = fv.normalize_frame(flo_data)
rgb_data = fv.flow_to_rgb(flo_data_norm)
background_attenuation = 0.0
flat_colors = True
arrow_color = (0, 0, 0)
else:
rgb_data = fv.input.rgb(rgb_dir)
background_attenuation = 0.4
flat_colors = False
arrow_color = 'flow'
arrow_data = fv.draw_flow_arrows(
rgb_data,
flo_data,
background_attenuation=background_attenuation,
color=arrow_color,
flat_colors=flat_colors,
arrow_min_alpha=0.7,
subsample_ratio=subsample_ratio,
ignore_ratio_warning=False)
# Generate output
if out_figure:
(framerate) = out_options
out = fv.output.show_plot(title='color_flow result',
framerate=framerate)
out.show_all(arrow_data, show_count=True)
else:
(framerate, out_name) = out_options
out = fv.output.video(out_name, framerate=framerate)
out.add_all(arrow_data, verbose=True)