def print_all(self):
if plt is None:
logger.log(('matplotlib', logger.Text.highlight),
' not found. So cannot display images')
images = [to_numpy(v) for v in self._values.values()]
images = np.concatenate(images)
n_images = len(images)
cols = max(1, int(math.sqrt(n_images)))
fig: plt.Figure
fig, axs = plt.subplots((n_images + cols - 1) // cols,
cols,
sharex='all',
sharey='all',
figsize=(8, 10))
fig.suptitle(self.name)
for i, img in enumerate(images):
if len(images) > 1:
ax: plt.Axes = axs[i // cols, i % cols]
else:
ax = axs
if img.shape[0] == 1:
img = img[0, :, :]
else:
img = img.transpose(1, 2, 0)
if img.dtype.type in (np.float32, np.float64):
img = np.clip(img, 0., 1.)
else:
img = np.clip(img, 0, 255)
ax.imshow(img)
plt.show()
def print_all(self):
if plt is None:
logger.log(('matplotlib', logger.Text.highlight),
' not found. So cannot display images')
images = [to_numpy(v) for v in self._values.values()]
cols = 3
fig: plt.Figure
fig, axs = plt.subplots((len(images) + cols - 1) // cols, cols,
sharex='all', sharey='all',
figsize=(8, 10))
fig.suptitle(self.name)
for i, img in enumerate(images):
ax: plt.Axes = axs[i // cols, i % cols]
ax.imshow(img)
plt.show()
def _collect_value(self, key: str, value):
self._values[key] = to_numpy(value)
def collect_value(self, value):
value = to_numpy(value).ravel()
if len(value) > 0:
self._values.append(to_numpy(value).ravel())
def collect_value(self, value):
self._is_empty = False
self._values.append(to_numpy(value).ravel())
def collect_value(self, value):
self._values.append(to_numpy(value).ravel())