def load_sprite_image(img_path, rows_cols, n_sprites=None):
'''Load a 2D (3D with color channels) sprite image where
(rows,cols) = rows_cols, slices, and returns as a 3D tensor (4D
with color channels). Sprite shape is computed automatically. If
n_sprites is not given, it is assumed to be rows*cols. Return as
3D tensor with shape (n_sprites, sprite_height, sprite_width,
sprite_channels).
'''
rows, cols = rows_cols
if n_sprites is None:
n_sprites = rows * cols
img = caffe_load_image(img_path, color=True, as_uint=True)
assert img.shape[
0] % rows == 0, 'sprite image has shape %s which is not divisible by rows_cols %' % (
img.shape, rows_cols)
assert img.shape[
1] % cols == 0, 'sprite image has shape %s which is not divisible by rows_cols %' % (
img.shape, rows_cols)
sprite_height = img.shape[0] / rows
sprite_width = img.shape[1] / cols
sprite_channels = img.shape[2]
ret = np.zeros((n_sprites, sprite_height, sprite_width, sprite_channels),
dtype=img.dtype)
for idx in xrange(n_sprites):
# Row-major order
ii = idx / cols
jj = idx % cols
ret[idx] = img[ii * sprite_height:(ii + 1) * sprite_height,
jj * sprite_width:(jj + 1) * sprite_width, :]
return ret
def load_sprite_image(img_path, rows_cols, n_sprites = None):
'''Load a 2D (3D with color channels) sprite image where
(rows,cols) = rows_cols, slices, and returns as a 3D tensor (4D
with color channels). Sprite shape is computed automatically. If
n_sprites is not given, it is assumed to be rows*cols. Return as
3D tensor with shape (n_sprites, sprite_height, sprite_width,
sprite_channels).
'''
rows,cols = rows_cols
if n_sprites is None:
n_sprites = rows * cols
img = caffe_load_image(img_path, color = True, as_uint = True)
assert img.shape[0] % rows == 0, 'sprite image has shape %s which is not divisible by rows_cols %' % (img.shape, rows_cols)
assert img.shape[1] % cols == 0, 'sprite image has shape %s which is not divisible by rows_cols %' % (img.shape, rows_cols)
sprite_height = img.shape[0] / rows
sprite_width = img.shape[1] / cols
sprite_channels = img.shape[2]
ret = np.zeros((n_sprites, sprite_height, sprite_width, sprite_channels), dtype = img.dtype)
for idx in xrange(n_sprites):
# Row-major order
ii = idx / cols
jj = idx % cols
ret[idx] = img[ii*sprite_height:(ii+1)*sprite_height,
jj*sprite_width:(jj+1)*sprite_width, :]
return ret
def get_image_from_files(settings, unit_folder_path, should_crop_to_corner, resize_shape, first_only, captions = [], values = []):
try:
# list unit images
unit_images_path = sorted(glob.glob(unit_folder_path))
mega_image = np.zeros((resize_shape[0], resize_shape[1], 3), dtype=np.uint8)
# if no images
if not unit_images_path:
return mega_image
if first_only:
unit_images_path = [unit_images_path[0]]
# load all images
unit_images = [caffe_load_image(unit_image_path, color=True, as_uint=True) for unit_image_path in
unit_images_path]
if settings.caffevis_clear_negative_activations:
# clear images with 0 value
if values:
for i in range(len(values)):
if values[i] < float_info.epsilon:
unit_images[i] *= 0
if should_crop_to_corner:
unit_images = [crop_to_corner(img, 2) for img in unit_images]
num_images = len(unit_images)
images_per_axis = int(np.math.ceil(np.math.sqrt(num_images)))
padding_pixel = 1
if first_only:
single_resized_image_shape = (resize_shape[0] - 2*padding_pixel, resize_shape[1] - 2*padding_pixel)
else:
single_resized_image_shape = ((resize_shape[0] / images_per_axis) - 2*padding_pixel, (resize_shape[1] / images_per_axis) - 2*padding_pixel)
unit_images = [ensure_uint255_and_resize_without_fit(unit_image, single_resized_image_shape) for unit_image in unit_images]
# build mega image
should_add_caption = (len(captions) == num_images)
defaults = {'face': settings.caffevis_score_face,
'fsize': settings.caffevis_score_fsize,
'clr': to_255(settings.caffevis_score_clr),
'thick': settings.caffevis_score_thick}
for i in range(num_images):
# add caption if we have exactly one for each image
if should_add_caption:
loc = settings.caffevis_score_loc[::-1] # Reverse to OpenCV c,r order
fs = FormattedString(captions[i], defaults)
cv2_typeset_text(unit_images[i], [[fs]], loc)
cell_row = i / images_per_axis
cell_col = i % images_per_axis
mega_image_height_start = 1 + cell_row * (single_resized_image_shape[0] + 2 * padding_pixel)
mega_image_height_end = mega_image_height_start + single_resized_image_shape[0]
mega_image_width_start = 1 + cell_col * (single_resized_image_shape[1] + 2 * padding_pixel)
mega_image_width_end = mega_image_width_start + single_resized_image_shape[1]
mega_image[mega_image_height_start:mega_image_height_end, mega_image_width_start:mega_image_width_end,:] = unit_images[i]
return mega_image
except:
print '\nAttempted to load files from %s but failed. ' % unit_folder_path
# set black image as place holder
return np.zeros((resize_shape[0], resize_shape[1], 3), dtype=np.uint8)
pass
return
def run(self):
print 'JPGVisLoadingThread.run called'
while not self.is_timed_out():
with self.state.lock:
if self.state.quit:
break
#print 'JPGVisLoadingThread.run: caffe_net_state is:', self.state.caffe_net_state
#print 'JPGVisLoadingThread.run loop: next_frame: %s, caffe_net_state: %s, back_enabled: %s' % (
# 'None' if self.state.next_frame is None else 'Avail',
# self.state.caffe_net_state,
# self.state.back_enabled)
jpgvis_to_load_key = self.state.jpgvis_to_load_key
if jpgvis_to_load_key is None:
time.sleep(self.loop_sleep)
continue
state_layer, state_selected_unit, data_shape = jpgvis_to_load_key
# Load three images:
images = [None] * 3
# Resize each component images only using one direction as
# a constraint. This is straightforward but could be very
# wasteful (making an image much larger then much smaller)
# if the proportions of the stacked image are very
# different from the proportions of the data pane.
#resize_shape = (None, data_shape[1]) if self.settings.caffevis_jpgvis_stack_vert else (data_shape[0], None)
# As a heuristic, instead just assume the three images are of the same shape.
if self.settings.caffevis_jpgvis_stack_vert:
resize_shape = (data_shape[0]/3, data_shape[1])
else:
resize_shape = (data_shape[0], data_shape[1]/3)
# 0. e.g. regularized_opt/conv1/conv1_0037_montage.jpg
jpg_path = os.path.join(self.settings.caffevis_unit_jpg_dir,
'regularized_opt',
state_layer,
'%s_%04d_montage.jpg' % (state_layer, state_selected_unit))
try:
img = caffe_load_image(jpg_path, color = True)
img_corner = crop_to_corner(img, 2)
images[0] = ensure_uint255_and_resize_to_fit(img_corner, resize_shape)
except IOError:
print '\nAttempted to load file %s but failed. To supress this warning, remove layer "%s" from settings.caffevis_jpgvis_layers' % (jpg_path, state_layer)
pass
# 1. e.g. max_im/conv1/conv1_0037.jpg
jpg_path = os.path.join(self.settings.caffevis_unit_jpg_dir,
'max_im',
state_layer,
'%s_%04d.jpg' % (state_layer, state_selected_unit))
try:
img = caffe_load_image(jpg_path, color=True)
images[1] = ensure_uint255_and_resize_to_fit(img, resize_shape)
except IOError:
print '\nAttempted to load file %s but failed.' % (jpg_path)
pass
# 2. e.g. max_deconv/conv1/conv1_0037.jpg
try:
jpg_path = os.path.join(self.settings.caffevis_unit_jpg_dir,
'max_deconv',
state_layer,
'%s_%04d.jpg' % (state_layer, state_selected_unit))
img = caffe_load_image(jpg_path, color = True)
images[2] = ensure_uint255_and_resize_to_fit(img, resize_shape)
except IOError:
pass
# Prune images that were not found:
images = [im for im in images if im is not None]
# Stack together
if len(images) > 0:
print 'Stacking:', [im.shape for im in images]
stack_axis = 0 if self.settings.caffevis_jpgvis_stack_vert else 1
img_stacked = np.concatenate(images, axis = stack_axis)
print 'Stacked:', img_stacked.shape
img_resize = ensure_uint255_and_resize_to_fit(img_stacked, data_shape)
print 'Resized:', img_resize.shape
else:
img_resize = np.zeros(shape=(0,)) # Sentinal value when image is not found.
self.cache.set(jpgvis_to_load_key, img_resize)
with self.state.lock:
self.state.jpgvis_to_load_key = None
self.state.drawing_stale = True
print 'JPGVisLoadingThread.run: finished'
def run(self):
print 'JPGVisLoadingThread.run called'
while not self.is_timed_out():
with self.state.lock:
if self.state.quit:
break
#print 'JPGVisLoadingThread.run: caffe_net_state is:', self.state.caffe_net_state
#print 'JPGVisLoadingThread.run loop: next_frame: %s, caffe_net_state: %s, back_enabled: %s' % (
# 'None' if self.state.next_frame is None else 'Avail',
# self.state.caffe_net_state,
# self.state.back_enabled)
jpgvis_to_load_key = self.state.jpgvis_to_load_key
if jpgvis_to_load_key is None:
time.sleep(self.loop_sleep)
continue
state_layer, state_selected_unit, data_shape = jpgvis_to_load_key
# Load three images:
images = [None] * 3
# Resize each component images only using one direction as
# a constraint. This is straightforward but could be very
# wasteful (making an image much larger then much smaller)
# if the proportions of the stacked image are very
# different from the proportions of the data pane.
#resize_shape = (None, data_shape[1]) if self.settings.caffevis_jpgvis_stack_vert else (data_shape[0], None)
# As a heuristic, instead just assume the three images are of the same shape.
if self.settings.caffevis_jpgvis_stack_vert:
resize_shape = (data_shape[0] / 3, data_shape[1])
else:
resize_shape = (data_shape[0], data_shape[1] / 3)
# 0. e.g. regularized_opt/conv1/conv1_0037_montage.jpg
jpg_path = os.path.join(
self.settings.caffevis_unit_jpg_dir, 'regularized_opt',
state_layer,
'%s_%04d_montage.jpg' % (state_layer, state_selected_unit))
try:
img = caffe_load_image(jpg_path, color=True)
img_corner = crop_to_corner(img, 2)
images[0] = ensure_uint255_and_resize_to_fit(
img_corner, resize_shape)
except IOError:
print '\nAttempted to load file %s but failed. To supress this warning, remove layer "%s" from settings.caffevis_jpgvis_layers' % (
jpg_path, state_layer)
pass
# 1. e.g. max_im/conv1/conv1_0037.jpg
jpg_path = os.path.join(
self.settings.caffevis_unit_jpg_dir, 'max_im', state_layer,
'%s_%04d.jpg' % (state_layer, state_selected_unit))
try:
img = caffe_load_image(jpg_path, color=True)
images[1] = ensure_uint255_and_resize_to_fit(img, resize_shape)
except IOError:
print '\nAttempted to load file %s but failed.' % (jpg_path)
pass
# 2. e.g. max_deconv/conv1/conv1_0037.jpg
try:
jpg_path = os.path.join(
self.settings.caffevis_unit_jpg_dir, 'max_deconv',
state_layer,
'%s_%04d.jpg' % (state_layer, state_selected_unit))
img = caffe_load_image(jpg_path, color=True)
images[2] = ensure_uint255_and_resize_to_fit(img, resize_shape)
except IOError:
pass
# Prune images that were not found:
images = [im for im in images if im is not None]
# Stack together
if len(images) > 0:
print 'Stacking:', [im.shape for im in images]
stack_axis = 0 if self.settings.caffevis_jpgvis_stack_vert else 1
img_stacked = np.concatenate(images, axis=stack_axis)
print 'Stacked:', img_stacked.shape
img_resize = ensure_uint255_and_resize_to_fit(
img_stacked, data_shape)
print 'Resized:', img_resize.shape
else:
img_resize = np.zeros(
shape=(0, )) # Sentinal value when image is not found.
self.cache.set(jpgvis_to_load_key, img_resize)
with self.state.lock:
self.state.jpgvis_to_load_key = None
self.state.drawing_stale = True
print 'JPGVisLoadingThread.run: finished'
