def _draw_status_pane(self, pane):
pane.data[:] = to_255(self.settings.window_background)
defaults = {'face': getattr(cv2, self.settings.caffevis_status_face),
'fsize': self.settings.caffevis_status_fsize,
'clr': to_255(self.settings.caffevis_status_clr),
'thick': self.settings.caffevis_status_thick}
loc = self.settings.caffevis_status_loc[::-1] # Reverse to OpenCV c,r order
status = StringIO.StringIO()
fps = self.proc_thread.approx_fps()
with self.state.lock:
print >>status, 'pattern' if self.state.pattern_mode else ('back' if self.state.layers_show_back else 'fwd'),
print >>status, '%s:%d |' % (self.state.layer, self.state.selected_unit),
if not self.state.back_enabled:
print >>status, 'Back: off',
else:
print >>status, 'Back: %s' % ('deconv' if self.state.back_mode == 'deconv' else 'bprop'),
print >>status, '(from %s_%d, disp %s)' % (self.state.backprop_layer,
self.state.backprop_unit,
self.state.back_filt_mode),
print >>status, '|',
print >>status, 'Boost: %g/%g' % (self.state.layer_boost_indiv, self.state.layer_boost_gamma)
if fps > 0:
print >>status, '| FPS: %.01f' % fps
if self.state.extra_msg:
print >>status, '|', self.state.extra_msg
self.state.extra_msg = ''
strings = [FormattedString(line, defaults) for line in status.getvalue().split('\n')]
cv2_typeset_text(pane.data, strings, loc,
line_spacing = self.settings.caffevis_status_line_spacing)
def _draw_prob_labels_pane(self, pane):
'''Adds text label annotation atop the given pane.'''
if not self.labels or not self.state.show_label_predictions or not self.settings.caffevis_prob_layer:
return
#pane.data[:] = to_255(self.settings.window_background)
defaults = {'face': getattr(cv2, self.settings.caffevis_class_face),
'fsize': self.settings.caffevis_class_fsize,
'clr': to_255(self.settings.caffevis_class_clr_0),
'thick': self.settings.caffevis_class_thick}
loc = self.settings.caffevis_class_loc[::-1] # Reverse to OpenCV c,r order
clr_0 = to_255(self.settings.caffevis_class_clr_0)
clr_1 = to_255(self.settings.caffevis_class_clr_1)
probs_flat = self.net.blobs[self.settings.caffevis_prob_layer].data.flatten()
top_5 = probs_flat.argsort()[-1:-6:-1]
strings = []
pmax = probs_flat[top_5[0]]
for idx in top_5:
prob = probs_flat[idx]
text = '%.2f %s' % (prob, self.labels[idx])
fs = FormattedString(text, defaults)
#fs.clr = tuple([clr_1[ii]*prob/pmax + clr_0[ii]*(1-prob/pmax) for ii in range(3)])
fs.clr = tuple([max(0,min(255,clr_1[ii]*prob + clr_0[ii]*(1-prob))) for ii in range(3)])
strings.append([fs]) # Line contains just fs
cv2_typeset_text(pane.data, strings, loc,
line_spacing = self.settings.caffevis_class_line_spacing)
def _draw_control_pane(self, pane):
pane.data[:] = to_255(self.settings.window_background)
with self.state.lock:
layer_idx = self.state.layer_idx
loc = self.settings.caffevis_control_loc[::-1] # Reverse to OpenCV c,r order
strings = []
defaults = {'face': getattr(cv2, self.settings.caffevis_control_face),
'fsize': self.settings.caffevis_control_fsize,
'clr': to_255(self.settings.caffevis_control_clr),
'thick': self.settings.caffevis_control_thick}
for ii in range(len(self.layer_print_names)):
fs = FormattedString(self.layer_print_names[ii], defaults)
this_layer = self.state._layers[ii]
if self.state.backprop_selection_frozen and this_layer == self.state.backprop_layer:
fs.clr = to_255(self.settings.caffevis_control_clr_bp)
fs.thick = self.settings.caffevis_control_thick_bp
if this_layer == self.state.layer:
if self.state.cursor_area == 'top':
fs.clr = to_255(self.settings.caffevis_control_clr_cursor)
fs.thick = self.settings.caffevis_control_thick_cursor
else:
if not (self.state.backprop_selection_frozen and this_layer == self.state.backprop_layer):
fs.clr = to_255(self.settings.caffevis_control_clr_selected)
fs.thick = self.settings.caffevis_control_thick_selected
strings.append(fs)
cv2_typeset_text(pane.data, strings, loc,
line_spacing = self.settings.caffevis_control_line_spacing,
wrap = True)
def draw_help(self):
self.help_buffer[:] *= .7
self.help_pane.data *= .7
#pane.data[:] = to_255(self.settings.window_background)
defaults = {
'face': getattr(cv2, self.settings.caffevis_help_face),
'fsize': self.settings.caffevis_help_fsize,
'clr': to_255(self.settings.caffevis_help_clr),
'thick': self.settings.caffevis_help_thick
}
loc = self.settings.caffevis_help_loc[::
-1] # Reverse to OpenCV c,r order
lines = []
lines.append([
FormattedString(
'~ ~ ~ Deep Visualization Toolbox ~ ~ ~',
defaults,
align='center',
width=self.help_pane.j_size)
])
lines.append([FormattedString('', defaults)])
lines.append([FormattedString('Base keys', defaults)])
#lines.append([FormattedString('lllll', defaults), FormattedString('WWWW', defaults)])
#lines.append([FormattedString('WWWWW', defaults), FormattedString('llll', defaults)])
#lines.append([FormattedString('lllll', defaults, width=150), FormattedString('WWWW', defaults, width=150)])
#lines.append([FormattedString('WWWWW', defaults, width=150), FormattedString('llll', defaults, width=150)])
#lines.append([FormattedString('AAA', defaults),
# FormattedString('left', defaults, width = 300),
# FormattedString('BBB', defaults)])
#lines.append([FormattedString('AAA', defaults),
# FormattedString('center', defaults, width = 300, align='center'),
# FormattedString('BBB', defaults)])
#lines.append([FormattedString('AAA', defaults),
# FormattedString('right', defaults, width = 300, align='right'),
# FormattedString('BBB', defaults)])
for tag in ('help_mode', 'freeze_cam', 'toggle_input_mode',
'static_file_increment', 'static_file_decrement',
'stretch_mode', 'quit'):
key_strings, help_string = self.bindings.get_key_help(tag)
label = '%10s:' % (','.join(key_strings))
lines.append([
FormattedString(label, defaults, width=120, align='right'),
FormattedString(help_string, defaults)
])
locy = cv2_typeset_text(
self.help_pane.data,
lines,
loc,
line_spacing=self.settings.caffevis_help_line_spacing)
for app_name, app in self.apps.iteritems():
locy = app.draw_help(self.help_pane, locy)
def draw_help(self):
self.help_buffer[:] *= 0.7
self.help_pane.data *= 0.7
# pane.data[:] = to_255(self.settings.window_background)
defaults = {
"face": getattr(cv2, self.settings.caffevis_help_face),
"fsize": self.settings.caffevis_help_fsize,
"clr": to_255(self.settings.caffevis_help_clr),
"thick": self.settings.caffevis_help_thick,
}
loc = self.settings.caffevis_help_loc[::-1] # Reverse to OpenCV c,r order
lines = []
lines.append(
[
FormattedString(
"~ ~ ~ Deep Visualization Toolbox ~ ~ ~", defaults, align="center", width=self.help_pane.j_size
)
]
)
lines.append([FormattedString("", defaults)])
lines.append([FormattedString("Base keys", defaults)])
# lines.append([FormattedString('lllll', defaults), FormattedString('WWWW', defaults)])
# lines.append([FormattedString('WWWWW', defaults), FormattedString('llll', defaults)])
# lines.append([FormattedString('lllll', defaults, width=150), FormattedString('WWWW', defaults, width=150)])
# lines.append([FormattedString('WWWWW', defaults, width=150), FormattedString('llll', defaults, width=150)])
# lines.append([FormattedString('AAA', defaults),
# FormattedString('left', defaults, width = 300),
# FormattedString('BBB', defaults)])
# lines.append([FormattedString('AAA', defaults),
# FormattedString('center', defaults, width = 300, align='center'),
# FormattedString('BBB', defaults)])
# lines.append([FormattedString('AAA', defaults),
# FormattedString('right', defaults, width = 300, align='right'),
# FormattedString('BBB', defaults)])
for tag in (
"help_mode",
"freeze_cam",
"toggle_input_mode",
"static_file_increment",
"static_file_decrement",
"stretch_mode",
"quit",
):
key_strings, help_string = self.bindings.get_key_help(tag)
label = "%10s:" % (",".join(key_strings))
lines.append(
[FormattedString(label, defaults, width=120, align="right"), FormattedString(help_string, defaults)]
)
locy = cv2_typeset_text(self.help_pane.data, lines, loc, line_spacing=self.settings.caffevis_help_line_spacing)
for app_name, app in self.apps.iteritems():
locy = app.draw_help(self.help_pane, locy)
def draw_help(self, help_pane, locy):
defaults = {'face': getattr(cv2, self.settings.help_face),
'fsize': self.settings.help_fsize,
'clr': to_255(self.settings.help_clr),
'thick': self.settings.help_thick}
loc_base = self.settings.help_loc[::-1] # Reverse to OpenCV c,r order
locx = loc_base[0]
lines = []
lines.append([FormattedString('', defaults)])
lines.append([FormattedString('Caffevis keys', defaults)])
kl,_ = self.bindings.get_key_help('sel_left')
kr,_ = self.bindings.get_key_help('sel_right')
ku,_ = self.bindings.get_key_help('sel_up')
kd,_ = self.bindings.get_key_help('sel_down')
klf,_ = self.bindings.get_key_help('sel_left_fast')
krf,_ = self.bindings.get_key_help('sel_right_fast')
kuf,_ = self.bindings.get_key_help('sel_up_fast')
kdf,_ = self.bindings.get_key_help('sel_down_fast')
keys_nav_0 = ','.join([kk[0] for kk in (kl, kr, ku, kd)])
keys_nav_1 = ''
if len(kl)>1 and len(kr)>1 and len(ku)>1 and len(kd)>1:
keys_nav_1 += ' or '
keys_nav_1 += ','.join([kk[1] for kk in (kl, kr, ku, kd)])
keys_nav_f = ','.join([kk[0] for kk in (klf, krf, kuf, kdf)])
nav_string = 'Navigate with %s%s. Use %s to move faster.' % (keys_nav_0, keys_nav_1, keys_nav_f)
lines.append([FormattedString('', defaults, width=120, align='right'),
FormattedString(nav_string, defaults)])
for tag in ('sel_layer_left', 'sel_layer_right', 'zoom_mode', 'pattern_mode',
'ez_back_mode_loop', 'freeze_back_unit', 'show_back', 'back_mode', 'back_filt_mode',
'boost_gamma', 'boost_individual', 'reset_state'):
key_strings, help_string = self.bindings.get_key_help(tag)
label = '%10s:' % (','.join(key_strings))
lines.append([FormattedString(label, defaults, width=120, align='right'),
FormattedString(help_string, defaults)])
locy = cv2_typeset_text(help_pane.data, lines, (locx, locy),
line_spacing = self.settings.help_line_spacing)
return locy
def draw_help(self):
self.help_buffer[:] = self.help_buffer[:] * .7
self.help_pane.data[:] = self.help_pane.data[:] * .7
loc = self.settings.help_loc[::-1] # Reverse to OpenCV c,r order
defaults = self.help_pane_defaults
lines = []
lines.append([FormattedString('~ ~ ~ Deep Visualization Toolbox ~ ~ ~', defaults, align='center', width=self.help_pane.j_size)])
lines.append([FormattedString('', defaults)])
lines.append([FormattedString('Base keys', defaults)])
for tag in ('help_mode', 'freeze_cam', 'toggle_input_mode', 'static_file_increment', 'static_file_decrement', 'stretch_mode', 'quit'):
key_strings, help_string = self.bindings.get_key_help(tag)
label = '%10s:' % (','.join(key_strings))
lines.append([FormattedString(label, defaults, width=120, align='right'),
FormattedString(help_string, defaults)])
locy = cv2_typeset_text(self.help_pane.data, lines, loc,
line_spacing = self.settings.help_line_spacing)
for app_name, app in self.apps.iteritems():
locy = app.draw_help(self.help_pane, locy)
def run_loop(self):
self.quit = False
# Setup
self.init_window()
#cap = cv2.VideoCapture(self.settings.capture_device)
self.input_updater = InputImageFetcher(self.settings)
self.input_updater.bind_camera()
self.input_updater.start()
heartbeat_functions = [self.input_updater.heartbeat]
for app_name, app in self.apps.iteritems():
print 'Starting app:', app_name
app.start()
heartbeat_functions.extend(app.get_heartbeats())
ii = 0
since_keypress = 999
since_redraw = 999
since_imshow = 0
last_render = time.time() - 999
latest_frame_idx = None
latest_frame_data = None
frame_for_apps = None
redraw_needed = True # Force redraw the first time
imshow_needed = True
while not self.quit:
# Call any heartbeats
for heartbeat in heartbeat_functions:
#print 'Heartbeat: calling', heartbeat
heartbeat()
# Handle key presses
keys = []
# Collect key presses (multiple if len(range)>1)
for cc in range(1):
with WithTimer('LiveVis:waitKey', quiet = self.debug_level < 2):
key = cv2.waitKey(self.settings.main_loop_sleep_ms)
if key == -1:
break
else:
keys.append(key)
#print 'Got key:', key
now = time.time()
#print 'Since last:', now - last_render
skip_imshow = False
#if now - last_render > .05 and since_imshow < 1:
# skip_imshow = True
if skip_imshow:
since_imshow += 1
else:
since_imshow = 0
last_render = now
#print ' Number of keys:', len(keys)
for key in keys:
since_keypress = 0
#print 'Got Key:', key
key,do_redraw = self.handle_key_pre_apps(key)
redraw_needed |= do_redraw
imshow_needed |= do_redraw
for app_name, app in self.apps.iteritems():
with WithTimer('%s:handle_key' % app_name, quiet = self.debug_level < 1):
key = app.handle_key(key, self.panes)
key = self.handle_key_post_apps(key)
if self.quit:
break
for app_name, app in self.apps.iteritems():
redraw_needed |= app.redraw_needed()
# Grab latest frame from input_updater thread
fr_idx,fr_data = self.input_updater.get_frame()
is_new_frame = (fr_idx != latest_frame_idx and fr_data is not None)
if is_new_frame:
latest_frame_idx = fr_idx
latest_frame_data = fr_data
frame_for_apps = fr_data
if is_new_frame:
with WithTimer('LiveVis.display_frame', quiet = self.debug_level < 1):
self.display_frame(latest_frame_data)
imshow_needed = True
do_handle_input = (ii == 0 or
since_keypress >= self.settings.keypress_pause_handle_iterations)
if frame_for_apps is not None and do_handle_input:
# Pass frame to apps for processing
for app_name, app in self.apps.iteritems():
with WithTimer('%s:handle_input' % app_name, quiet = self.debug_level < 1):
app.handle_input(latest_frame_data, self.panes)
frame_for_apps = None
# Tell each app to draw
do_redraw = (redraw_needed and
(since_keypress >= self.settings.keypress_pause_redraw_iterations or
since_redraw >= self.settings.redraw_at_least_every))
if redraw_needed and do_redraw:
for app_name, app in self.apps.iteritems():
with WithTimer('%s:draw' % app_name, quiet = self.debug_level < 1):
imshow_needed |= app.draw(self.panes)
redraw_needed = False
since_redraw = 0
# Render buffer
if imshow_needed:
# Only redraw pane debug if display will be updated
if hasattr(self.settings, 'debug_window_panes') and self.settings.debug_window_panes:
for pane_name,pane in self.panes.iteritems():
print pane_name, pane
pane.data[:] = pane.data * .5
line = [FormattedString('%s |' % pane_name, self.debug_pane_defaults),
FormattedString('pos: %d,%d |' % (pane.i_begin, pane.j_begin), self.debug_pane_defaults),
FormattedString('shape: %d,%d' % (pane.i_size, pane.j_size), self.debug_pane_defaults)]
cv2_typeset_text(pane.data, line, (5,20), line_spacing = 5, wrap = True)
pane.data[:1,:] = pane_debug_clr
pane.data[-1:,:] = pane_debug_clr
pane.data[:,:1] = pane_debug_clr
pane.data[:,-1:] = pane_debug_clr
with WithTimer('LiveVis:imshow', quiet = self.debug_level < 1):
if self.help_mode:
# Copy main buffer to help buffer
self.help_buffer[:] = self.window_buffer[:]
self.draw_help()
cv2_imshow_rgb(self.window_name, self.help_buffer)
else:
cv2_imshow_rgb(self.window_name, self.window_buffer)
imshow_needed = False
ii += 1
since_keypress += 1
since_redraw += 1
if ii % 2 == 0 and self.settings.print_dots:
sys.stdout.write('.')
sys.stdout.flush()
# Extra sleep just for debugging. In production all main loop sleep should be in cv2.waitKey.
#time.sleep(2)
print '\n\nTrying to exit run_loop...'
self.input_updater.quit = True
self.input_updater.join(.01 + float(self.settings.input_updater_sleep_after_read_frame) * 5)
if self.input_updater.is_alive():
raise Exception('Could not join self.input_updater thread')
else:
self.input_updater.free_camera()
for app_name, app in self.apps.iteritems():
print 'Quitting app:', app_name
app.quit()
print 'Input thread joined and apps quit; exiting run_loop.'
def _draw_layer_pane(self, pane):
'''Returns the data shown in highres format, b01c order.'''
if self.state.layers_show_back:
layer_dat_3D = self.net.blobs[self.state.layer].diff[0]
else:
layer_dat_3D = self.net.blobs[self.state.layer].data[0]
# Promote FC layers with shape (n) to have shape (n,1,1)
if len(layer_dat_3D.shape) == 1:
layer_dat_3D = layer_dat_3D[:,np.newaxis,np.newaxis]
n_tiles = layer_dat_3D.shape[0]
tile_rows,tile_cols = self.net_layer_info[self.state.layer]['tiles_rc']
display_3D_highres = None
if self.state.pattern_mode:
# Show desired patterns loaded from disk
load_layer = self.state.layer
if self.settings.caffevis_jpgvis_remap and self.state.layer in self.settings.caffevis_jpgvis_remap:
load_layer = self.settings.caffevis_jpgvis_remap[self.state.layer]
if self.settings.caffevis_jpgvis_layers and load_layer in self.settings.caffevis_jpgvis_layers:
jpg_path = os.path.join(self.settings.caffevis_unit_jpg_dir,
'regularized_opt', load_layer, 'whole_layer.jpg')
# Get highres version
#cache_before = str(self.img_cache)
display_3D_highres = self.img_cache.get((jpg_path, 'whole'), None)
#else:
# display_3D_highres = None
if display_3D_highres is None:
try:
with WithTimer('CaffeVisApp:load_sprite_image', quiet = self.debug_level < 1):
display_3D_highres = load_square_sprite_image(jpg_path, n_sprites = n_tiles)
except IOError:
# File does not exist, so just display disabled.
pass
else:
self.img_cache.set((jpg_path, 'whole'), display_3D_highres)
#cache_after = str(self.img_cache)
#print 'Cache was / is:\n %s\n %s' % (cache_before, cache_after)
if display_3D_highres is not None:
# Get lowres version, maybe. Assume we want at least one pixel for selection border.
row_downsamp_factor = int(np.ceil(float(display_3D_highres.shape[1]) / (pane.data.shape[0] / tile_rows - 2)))
col_downsamp_factor = int(np.ceil(float(display_3D_highres.shape[2]) / (pane.data.shape[1] / tile_cols - 2)))
ds = max(row_downsamp_factor, col_downsamp_factor)
if ds > 1:
#print 'Downsampling by', ds
display_3D = display_3D_highres[:,::ds,::ds,:]
else:
display_3D = display_3D_highres
else:
display_3D = layer_dat_3D * 0 # nothing to show
else:
# Show data from network (activations or diffs)
if self.state.layers_show_back:
back_what_to_disp = self.get_back_what_to_disp()
if back_what_to_disp == 'disabled':
layer_dat_3D_normalized = np.tile(self.settings.window_background, layer_dat_3D.shape + (1,))
elif back_what_to_disp == 'stale':
layer_dat_3D_normalized = np.tile(self.settings.stale_background, layer_dat_3D.shape + (1,))
else:
layer_dat_3D_normalized = tile_images_normalize(layer_dat_3D,
boost_indiv = self.state.layer_boost_indiv,
boost_gamma = self.state.layer_boost_gamma,
neg_pos_colors = ((1,0,0), (0,1,0)))
else:
layer_dat_3D_normalized = tile_images_normalize(layer_dat_3D,
boost_indiv = self.state.layer_boost_indiv,
boost_gamma = self.state.layer_boost_gamma)
#print ' ===layer_dat_3D_normalized.shape', layer_dat_3D_normalized.shape, 'layer_dat_3D_normalized dtype', layer_dat_3D_normalized.dtype, 'range', layer_dat_3D_normalized.min(), layer_dat_3D_normalized.max()
display_3D = layer_dat_3D_normalized
# Convert to float if necessary:
display_3D = ensure_float01(display_3D)
# Upsample gray -> color if necessary
# e.g. (1000,32,32) -> (1000,32,32,3)
if len(display_3D.shape) == 3:
display_3D = display_3D[:,:,:,np.newaxis]
if display_3D.shape[3] == 1:
display_3D = np.tile(display_3D, (1, 1, 1, 3))
# Upsample unit length tiles to give a more sane tile / highlight ratio
# e.g. (1000,1,1,3) -> (1000,3,3,3)
if display_3D.shape[1] == 1:
display_3D = np.tile(display_3D, (1, 3, 3, 1))
if self.state.layers_show_back and not self.state.pattern_mode:
padval = self.settings.caffevis_layer_clr_back_background
else:
padval = self.settings.window_background
highlights = [None] * n_tiles
with self.state.lock:
if self.state.cursor_area == 'bottom':
highlights[self.state.selected_unit] = self.settings.caffevis_layer_clr_cursor # in [0,1] range
if self.state.backprop_selection_frozen and self.state.layer == self.state.backprop_layer:
highlights[self.state.backprop_unit] = self.settings.caffevis_layer_clr_back_sel # in [0,1] range
_, display_2D = tile_images_make_tiles(display_3D, hw = (tile_rows,tile_cols), padval = padval, highlights = highlights)
if display_3D_highres is None:
display_3D_highres = display_3D
# Display pane based on layers_pane_zoom_mode
state_layers_pane_zoom_mode = self.state.layers_pane_zoom_mode
assert state_layers_pane_zoom_mode in (0,1,2)
if state_layers_pane_zoom_mode == 0:
# Mode 0: normal display (activations or patterns)
display_2D_resize = ensure_uint255_and_resize_to_fit(display_2D, pane.data.shape)
elif state_layers_pane_zoom_mode == 1:
# Mode 1: zoomed selection
unit_data = display_3D_highres[self.state.selected_unit]
display_2D_resize = ensure_uint255_and_resize_to_fit(unit_data, pane.data.shape)
else:
# Mode 2: zoomed backprop pane
display_2D_resize = ensure_uint255_and_resize_to_fit(display_2D, pane.data.shape) * 0
pane.data[:] = to_255(self.settings.window_background)
pane.data[0:display_2D_resize.shape[0], 0:display_2D_resize.shape[1], :] = display_2D_resize
if self.settings.caffevis_label_layers and self.state.layer in self.settings.caffevis_label_layers and self.labels and self.state.cursor_area == 'bottom':
# Display label annotation atop layers pane (e.g. for fc8/prob)
defaults = {'face': getattr(cv2, self.settings.caffevis_label_face),
'fsize': self.settings.caffevis_label_fsize,
'clr': to_255(self.settings.caffevis_label_clr),
'thick': self.settings.caffevis_label_thick}
loc_base = self.settings.caffevis_label_loc[::-1] # Reverse to OpenCV c,r order
lines = [FormattedString(self.labels[self.state.selected_unit], defaults)]
cv2_typeset_text(pane.data, lines, loc_base)
return display_3D_highres
def _draw_layer_pane(self, pane):
'''Returns the data shown in highres format, b01c order.'''
if self.state.layers_show_back:
layer_dat_3D = self.net.blobs[self.state.layer].diff[0]
else:
layer_dat_3D = self.net.blobs[self.state.layer].data[0]
# Promote FC layers with shape (n) to have shape (n,1,1)
if len(layer_dat_3D.shape) == 1:
layer_dat_3D = layer_dat_3D[:, np.newaxis, np.newaxis]
n_tiles = layer_dat_3D.shape[0]
tile_rows, tile_cols = self.net_layer_info[
self.state.layer]['tiles_rc']
display_3D_highres = None
if self.state.pattern_mode:
# Show desired patterns loaded from disk
load_layer = self.state.layer
if self.settings.caffevis_jpgvis_remap and self.state.layer in self.settings.caffevis_jpgvis_remap:
load_layer = self.settings.caffevis_jpgvis_remap[
self.state.layer]
if self.settings.caffevis_jpgvis_layers and load_layer in self.settings.caffevis_jpgvis_layers:
jpg_path = os.path.join(self.settings.caffevis_unit_jpg_dir,
'regularized_opt', load_layer,
'whole_layer.jpg')
# Get highres version
#cache_before = str(self.img_cache)
display_3D_highres = self.img_cache.get((jpg_path, 'whole'),
None)
#else:
# display_3D_highres = None
if display_3D_highres is None:
try:
with WithTimer('CaffeVisApp:load_sprite_image',
quiet=self.debug_level < 1):
display_3D_highres = load_square_sprite_image(
jpg_path, n_sprites=n_tiles)
except IOError:
# File does not exist, so just display disabled.
pass
else:
self.img_cache.set((jpg_path, 'whole'),
display_3D_highres)
#cache_after = str(self.img_cache)
#print 'Cache was / is:\n %s\n %s' % (cache_before, cache_after)
if display_3D_highres is not None:
# Get lowres version, maybe. Assume we want at least one pixel for selection border.
row_downsamp_factor = int(
np.ceil(
float(display_3D_highres.shape[1]) /
(pane.data.shape[0] / tile_rows - 2)))
col_downsamp_factor = int(
np.ceil(
float(display_3D_highres.shape[2]) /
(pane.data.shape[1] / tile_cols - 2)))
ds = max(row_downsamp_factor, col_downsamp_factor)
if ds > 1:
#print 'Downsampling by', ds
display_3D = display_3D_highres[:, ::ds, ::ds, :]
else:
display_3D = display_3D_highres
else:
display_3D = layer_dat_3D * 0 # nothing to show
else:
# Show data from network (activations or diffs)
if self.state.layers_show_back:
back_what_to_disp = self.get_back_what_to_disp()
if back_what_to_disp == 'disabled':
layer_dat_3D_normalized = np.tile(
self.settings.window_background,
layer_dat_3D.shape + (1, ))
elif back_what_to_disp == 'stale':
layer_dat_3D_normalized = np.tile(
self.settings.stale_background,
layer_dat_3D.shape + (1, ))
else:
layer_dat_3D_normalized = tile_images_normalize(
layer_dat_3D,
boost_indiv=self.state.layer_boost_indiv,
boost_gamma=self.state.layer_boost_gamma,
neg_pos_colors=((1, 0, 0), (0, 1, 0)))
else:
layer_dat_3D_normalized = tile_images_normalize(
layer_dat_3D,
boost_indiv=self.state.layer_boost_indiv,
boost_gamma=self.state.layer_boost_gamma)
#print ' ===layer_dat_3D_normalized.shape', layer_dat_3D_normalized.shape, 'layer_dat_3D_normalized dtype', layer_dat_3D_normalized.dtype, 'range', layer_dat_3D_normalized.min(), layer_dat_3D_normalized.max()
display_3D = layer_dat_3D_normalized
# Convert to float if necessary:
display_3D = ensure_float01(display_3D)
# Upsample gray -> color if necessary
# e.g. (1000,32,32) -> (1000,32,32,3)
if len(display_3D.shape) == 3:
display_3D = display_3D[:, :, :, np.newaxis]
if display_3D.shape[3] == 1:
display_3D = np.tile(display_3D, (1, 1, 1, 3))
# Upsample unit length tiles to give a more sane tile / highlight ratio
# e.g. (1000,1,1,3) -> (1000,3,3,3)
if display_3D.shape[1] == 1:
display_3D = np.tile(display_3D, (1, 3, 3, 1))
if self.state.layers_show_back and not self.state.pattern_mode:
padval = self.settings.caffevis_layer_clr_back_background
else:
padval = self.settings.window_background
highlights = [None] * n_tiles
with self.state.lock:
if self.state.cursor_area == 'bottom':
highlights[
self.state.
selected_unit] = self.settings.caffevis_layer_clr_cursor # in [0,1] range
if self.state.backprop_selection_frozen and self.state.layer == self.state.backprop_layer:
highlights[
self.state.
backprop_unit] = self.settings.caffevis_layer_clr_back_sel # in [0,1] range
_, display_2D = tile_images_make_tiles(display_3D,
hw=(tile_rows, tile_cols),
padval=padval,
highlights=highlights)
if display_3D_highres is None:
display_3D_highres = display_3D
# Display pane based on layers_pane_zoom_mode
state_layers_pane_zoom_mode = self.state.layers_pane_zoom_mode
assert state_layers_pane_zoom_mode in (0, 1, 2)
if state_layers_pane_zoom_mode == 0:
# Mode 0: normal display (activations or patterns)
display_2D_resize = ensure_uint255_and_resize_to_fit(
display_2D, pane.data.shape)
elif state_layers_pane_zoom_mode == 1:
# Mode 1: zoomed selection
unit_data = display_3D_highres[self.state.selected_unit]
display_2D_resize = ensure_uint255_and_resize_to_fit(
unit_data, pane.data.shape)
else:
# Mode 2: zoomed backprop pane
display_2D_resize = ensure_uint255_and_resize_to_fit(
display_2D, pane.data.shape) * 0
pane.data[:] = to_255(self.settings.window_background)
pane.data[0:display_2D_resize.shape[0],
0:display_2D_resize.shape[1], :] = display_2D_resize
if self.settings.caffevis_label_layers and self.state.layer in self.settings.caffevis_label_layers and self.labels and self.state.cursor_area == 'bottom':
# Display label annotation atop layers pane (e.g. for fc8/prob)
defaults = {
'face': getattr(cv2, self.settings.caffevis_label_face),
'fsize': self.settings.caffevis_label_fsize,
'clr': to_255(self.settings.caffevis_label_clr),
'thick': self.settings.caffevis_label_thick
}
loc_base = self.settings.caffevis_label_loc[::
-1] # Reverse to OpenCV c,r order
lines = [
FormattedString(self.labels[self.state.selected_unit],
defaults)
]
cv2_typeset_text(pane.data, lines, loc_base)
return display_3D_highres
def run_loop(self):
self.quit = False
# Setup
self.init_window()
#cap = cv2.VideoCapture(self.settings.capture_device)
self.input_updater = InputImageFetcher(self.settings)
self.input_updater.bind_camera()
self.input_updater.start()
heartbeat_functions = [self.input_updater.heartbeat]
for app_name, app in self.apps.iteritems():
print 'Starting app:', app_name
app.start()
heartbeat_functions.extend(app.get_heartbeats())
ii = 0
since_keypress = 999
since_redraw = 999
since_imshow = 0
last_render = time.time() - 999
latest_frame_idx = None
latest_frame_data = None
frame_for_apps = None
redraw_needed = True # Force redraw the first time
imshow_needed = True
count = 0
while not self.quit:
# Call any heartbeats
for heartbeat in heartbeat_functions:
#print 'Heartbeat: calling', heartbeat
heartbeat()
# Handle key presses
keys = []
# Collect key presses (multiple if len(range)>1)
for cc in range(1):
with WithTimer('LiveVis:waitKey', quiet=self.debug_level < 2):
key = cv2.waitKey(self.settings.main_loop_sleep_ms)
if key == -1:
break
else:
keys.append(key)
#print 'Got key:', key
now = time.time()
#print 'Since last:', now - last_render
skip_imshow = False
#if now - last_render > .05 and since_imshow < 1:
# skip_imshow = True
if skip_imshow:
since_imshow += 1
else:
since_imshow = 0
last_render = now
#print ' Number of keys:', len(keys)
for key in keys:
since_keypress = 0
#print 'Got Key:', key
key, do_redraw = self.handle_key_pre_apps(key)
redraw_needed |= do_redraw
imshow_needed |= do_redraw
for app_name, app in self.apps.iteritems():
with WithTimer('%s:handle_key' % app_name,
quiet=self.debug_level < 1):
key = app.handle_key(key, self.panes)
key = self.handle_key_post_apps(key)
if self.quit:
break
for app_name, app in self.apps.iteritems():
redraw_needed |= app.redraw_needed()
# Grab latest frame from input_updater thread
fr_idx, fr_data = self.input_updater.get_frame()
is_new_frame = (fr_idx != latest_frame_idx and fr_data is not None)
if is_new_frame:
latest_frame_idx = fr_idx
latest_frame_data = fr_data
frame_for_apps = fr_data
if is_new_frame:
with WithTimer('LiveVis.display_frame',
quiet=self.debug_level < 1):
self.display_frame(latest_frame_data)
imshow_needed = True
do_handle_input = (ii == 0 or since_keypress >=
self.settings.keypress_pause_handle_iterations)
if frame_for_apps is not None and do_handle_input:
# Pass frame to apps for processing
for app_name, app in self.apps.iteritems():
with WithTimer('%s:handle_input' % app_name,
quiet=self.debug_level < 1):
app.handle_input(latest_frame_data, self.panes)
frame_for_apps = None
# Tell each app to draw
do_redraw = (redraw_needed and
(since_keypress >=
self.settings.keypress_pause_redraw_iterations or
since_redraw >= self.settings.redraw_at_least_every))
if redraw_needed and do_redraw:
for app_name, app in self.apps.iteritems():
with WithTimer('%s:draw' % app_name,
quiet=self.debug_level < 1):
imshow_needed |= app.draw(self.panes)
redraw_needed = False
since_redraw = 0
# Render buffer
if imshow_needed:
# Only redraw pane debug if display will be updated
if hasattr(self.settings, 'debug_window_panes'
) and self.settings.debug_window_panes:
for pane_name, pane in self.panes.iteritems():
print pane_name, pane
pane.data[:] = pane.data * .5
line = [
FormattedString('%s |' % pane_name,
self.debug_pane_defaults),
FormattedString(
'pos: %d,%d |' % (pane.i_begin, pane.j_begin),
self.debug_pane_defaults),
FormattedString(
'shape: %d,%d' % (pane.i_size, pane.j_size),
self.debug_pane_defaults)
]
cv2_typeset_text(pane.data,
line, (5, 20),
line_spacing=5,
wrap=True)
pane.data[:1, :] = pane_debug_clr
pane.data[-1:, :] = pane_debug_clr
pane.data[:, :1] = pane_debug_clr
pane.data[:, -1:] = pane_debug_clr
with WithTimer('LiveVis:imshow', quiet=self.debug_level < 1):
if self.help_mode:
# Copy main buffer to help buffer
self.help_buffer[:] = self.window_buffer[:]
self.draw_help()
cv2_imshow_rgb(self.window_name, self.help_buffer,
True)
else:
if count == 0:
cv2_imshow_rgb(self.window_name,
self.window_buffer, False)
if count == 1:
cv2_imshow_rgb(self.window_name,
self.window_buffer, True)
break
count += 1
imshow_needed = False
ii += 1
since_keypress += 1
since_redraw += 1
if ii % 2 == 0 and self.settings.print_dots:
sys.stdout.write('.')
sys.stdout.flush()
# Extra sleep just for debugging. In production all main loop sleep should be in cv2.waitKey.
#time.sleep(2)
print '\n\nTrying to exit run_loop...'
self.input_updater.quit = True
self.input_updater.join(
.01 +
float(self.settings.input_updater_sleep_after_read_frame) * 5)
if self.input_updater.is_alive():
raise Exception('Could not join self.input_updater thread')
else:
self.input_updater.free_camera()
for app_name, app in self.apps.iteritems():
print 'Quitting app:', app_name
app.quit()
print 'Input thread joined and apps quit; exiting run_loop.'
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
