def render_func(viewer, start_frame, end_frame):
with lock:
saver = neuroglancer.ScreenshotSaver(viewer, args.output_directory)
for i in range(len(keypoints) - 1):
a = keypoints[i]['state']
b = keypoints[i + 1]['state']
duration = keypoints[i]['transition_duration']
num_frames = max(1, int(duration * fps))
for frame_i in range(num_frames):
t = frame_i / num_frames
index, path = saver.get_next_path()
if index >= end_frame:
return
if index < start_frame:
saver.index += 1
continue
if args.resume and os.path.exists(path):
saver.index += 1
with lock:
num_frames_written[0] += 1
else:
cur_state = neuroglancer.ViewerState.interpolate(a, b, t)
viewer.set_state(cur_state)
index, path = saver.capture()
with lock:
num_frames_written[0] += 1
cur_num_frames_written = num_frames_written[0]
print('[%07d/%07d] keypoint %.3f/%5d: %s' %
(cur_num_frames_written, total_frames, i + t,
len(keypoints), path))
def run_render(args):
keypoints = load_script(args.script)
viewer = neuroglancer.Viewer()
print('Open the specified URL to begin rendering')
print(viewer)
if args.browser:
webbrowser.open_new(viewer.get_viewer_url())
fps = args.fps
with viewer.config_state.txn() as s:
s.show_ui_controls = False
s.show_panel_borders = False
s.viewer_size = [args.width, args.height]
saver = neuroglancer.ScreenshotSaver(viewer, args.output_directory)
total_frames = sum(max(1, k['transition_duration'] * fps) for k in keypoints[:-1])
for i in range(len(keypoints) - 1):
a = keypoints[i]['state']
b = keypoints[i + 1]['state']
duration = keypoints[i]['transition_duration']
num_frames = max(1, int(duration * fps))
for frame_i in range(num_frames):
t = frame_i / num_frames
cur_state = neuroglancer.ViewerState.interpolate(a, b, t)
viewer.set_state(cur_state)
index, path = saver.capture()
print('[%07d/%07d] keypoint %.3f/%5d: %s' % (index, total_frames, i + t, len(keypoints), path))
def render_func(viewer, start_frame, end_frame):
with lock:
saver = neuroglancer.ScreenshotSaver(viewer, args.output_directory)
states_to_capture = []
frame_number = 0
for i in range(len(keypoints) - 1):
a = keypoints[i]['state']
b = keypoints[i + 1]['state']
duration = keypoints[i]['transition_duration']
num_frames = max(1, int(duration * fps))
for frame_i in range(num_frames):
t = frame_i / num_frames
if frame_number >= end_frame:
return
if frame_number < start_frame:
frame_number += 1
continue
path = saver.get_path(frame_number)
if args.resume and os.path.exists(path):
frame_number += 1
with lock:
num_frames_written[0] += 1
else:
cur_state = neuroglancer.ViewerState.interpolate(a, b, t)
states_to_capture.append((frame_number, i + t, cur_state))
frame_number += 1
for frame_number, t, cur_state in states_to_capture:
prefetch_states = [
x[2] for x in states_to_capture[frame_number + 1:frame_number +
1 + num_prefetch_frames]
]
prev_state = viewer.state.to_json()
cur_state = cur_state.to_json()
cur_state['layers'] = prev_state['layers']
cur_state = neuroglancer.ViewerState(cur_state)
viewer.set_state(cur_state)
if num_prefetch_frames > 0:
with viewer.config_state.txn() as s:
del s.prefetch[:]
for i, state in enumerate(prefetch_states[1:]):
s.prefetch.append(
neuroglancer.PrefetchState(
state=state, priority=num_prefetch_frames - i))
frame_number, path = saver.capture(frame_number)
with lock:
num_frames_written[0] += 1
cur_num_frames_written = num_frames_written[0]
print('[%07d/%07d] keypoint %.3f/%5d: %s' %
(cur_num_frames_written, total_frames, t, len(keypoints),
path))
s.layers["%s_atlas" % brainname] = neuroglancer.SegmentationLayer(
source="precomputed://http://localhost:%s" % int(port + 1))
print(viewer)
#this should add the atlas volume to the neuroglancer window
###WINDOW 3###
#take screenshots
#NOTE: THIS DOESN'T WORK IN A SPYDER, CONSOLE, ACTIVATE ENV AND RUN IN IPYTHON SHELL
import os
svdst = "/home/wanglab/Desktop/%s/cortex_wo_overlay_zoom " % brainname
#make sure these directories exist
if not os.path.exists(os.path.dirname(svdst)):
os.mkdir(os.path.dirname(svdst)) #brain directory
if not os.path.exists(svdst): os.mkdir(svdst) #structure directory
ss = neuroglancer.ScreenshotSaver(viewer, svdst)
with viewer.config_state.txn() as s:
s.show_ui_controls = False
s.show_panel_borders = False
for i in range(2700, 4000, 30):
if i % 10 == 0: print(i)
with viewer.txn() as s:
s.voxel_coordinates = [
1787, i, 442
] #the xy coords here are from the neuroglancer window
#(where the L center scale is located)
#optionally limit window size
# with viewer.config_state.txn() as s:
# s.viewer_size = [1000,1000]
ss.capture(index=i)