def show(**kwargs):
from vmaf import plt
import matplotlib
if matplotlib.rcParams['backend'] == 'agg':
if 'write_to_dir' in kwargs:
format = kwargs['format'] if 'format' in kwargs else 'png'
filedir = kwargs['write_to_dir'] if kwargs[
'write_to_dir'] is not None else VmafConfig.workspace_path(
'output')
os.makedirs(filedir, exist_ok=True)
for fignum in plt.get_fignums():
fig = plt.figure(fignum)
fig.savefig(os.path.join(filedir,
str(fignum) + '.' + format),
format=format)
else:
format = 'png'
filedir = VmafConfig.workspace_path('output')
os.makedirs(filedir, exist_ok=True)
for fignum in plt.get_fignums():
fig = plt.figure(fignum)
fig.savefig(os.path.join(filedir,
str(fignum) + '.' + format),
format=format)
else:
plt.show()
def show(**kwargs):
from vmaf import plt
if 'write_to_dir' in kwargs:
format = kwargs['format'] if 'format' in kwargs else 'png'
filedir = kwargs['write_to_dir'] if kwargs['write_to_dir'] is not None else VmafConfig.workspace_path('output')
if not os.path.exists(filedir):
os.makedirs(filedir)
for fignum in plt.get_fignums():
fig = plt.figure(fignum)
fig.savefig(os.path.join(filedir, str(fignum) + '.' + format), format=format)
else:
plt.show()
def plot_explanations(cls, exps, assets=None, ys=None, ys_pred=None):
# asserts
N = cls.assert_explanations(exps, assets, ys, ys_pred)
figs = []
for n in range(N):
weights = exps['feature_weights'][n]
features = exps['features'][n]
normalized = exps['features_normalized'][n]
asset = assets[n] if assets is not None else None
y = ys['label'][n] if ys is not None else None
y_pred = ys_pred[n] if ys_pred is not None else None
img = None
if asset is not None:
w, h = asset.dis_width_height
with YuvReader(filepath=asset.dis_path,
width=w,
height=h,
yuv_type=asset.dis_yuv_type) as yuv_reader:
for yuv in yuv_reader:
img, _, _ = yuv
break
assert img is not None
title = ""
if asset is not None:
title += "{}\n".format(
get_file_name_without_extension(asset.ref_path))
if y is not None:
title += "ground truth: {:.3f}\n".format(y)
if y_pred is not None:
title += "predicted: {:.3f}\n".format(y_pred)
if title != "" and title[-1] == '\n':
title = title[:-1]
assert len(weights) == len(features)
M = len(weights)
fig = plt.figure()
ax_top = plt.subplot(2, 1, 1)
ax_left = plt.subplot(2, 3, 4)
ax_mid = plt.subplot(2, 3, 5, sharey=ax_left)
ax_right = plt.subplot(2, 3, 6, sharey=ax_left)
if img is not None:
ax_top.imshow(img, cmap='Greys_r')
ax_top.get_xaxis().set_visible(False)
ax_top.get_yaxis().set_visible(False)
ax_top.set_title(title)
pos = np.arange(M) + 0.1
ax_left.barh(pos, features, color='b', label='feature')
ax_left.set_xticks(np.arange(0, 1.1, 0.2))
ax_left.set_yticks(pos + 0.35)
ax_left.set_yticklabels(exps['feature_names'])
ax_left.set_title('feature')
ax_mid.barh(pos, normalized, color='g', label='fnormal')
ax_mid.get_yaxis().set_visible(False)
ax_mid.set_title('fnormal')
ax_right.barh(pos, weights, color='r', label='weight')
ax_right.get_yaxis().set_visible(False)
ax_right.set_title('weight')
plt.tight_layout()
figs.append(fig)
return figs
