def hv_adjust_image_landmarks(image,
landmarks,
landmarks_match=None,
bregma_offset=None,
resolution=0.0194,
msize=40):
'''
TODO: merge part of this with the one for the landmarks
landmarks are in allen reference space
'''
h, w = image.shape
if bregma_offset is None:
# then it is the center of the image
bregma_offset = np.array([int(w / 2), int(h / 2)
]) # place bregma in the center of the image
landmarks_im = allen_landmarks_to_image_space(landmarks.copy(),
bregma_offset, resolution)
if landmarks_match is None:
landmarks_match = landmarks_im
import holoviews as hv
from holoviews import opts, streams
from holoviews.plotting.links import DataLink
bounds = np.array([0, 0, w, h])
im = hv.Image(image[::-1, :],
bounds=tuple(bounds.tolist())).opts(invert_yaxis=True,
cmap='gray')
points = hv.Points(landmarks_match, vdims='color').opts(marker='+',
size=msize)
point_stream = streams.PointDraw(data=points.columns(),
add=False,
num_objects=4,
source=points,
empty_value='black')
table = hv.Table(points, ['x', 'y', 'name'],
'color').opts(title='Annotation location')
DataLink(points, table)
from bokeh.models import HoverTool
hoverpts = HoverTool(tooltips=[("i", "$index")])
widget = (im * points + table).opts(
opts.Layout(merge_tools=False),
opts.Points(invert_yaxis=True,
active_tools=['point_draw'],
color='color',
tools=[hoverpts],
width=int(w),
height=int(h)), opts.Table(editable=True))
return widget, point_stream, landmarks_im
def hv_adjust_reference_landmarks(landmarks, ccf_regions, msize=40):
'''
landmarks = {'x': [-1.95, 0, 1.95, 0],
'y': [-3.45, -3.45, -3.45, 3.2],
'name': ['OB_left', 'OB_center', 'OB_right', 'RSP_base'],
'color': ['#fc9d03', '#0367fc', '#fc9d03', '#fc4103']}
landmarks = pd.DataFrame(landmarks)
# adjust landmarks
wid,landmark_wid = hv_adjust_reference_landmarks(landmarks,ccf_regions)
wid # to display
# use the following to retrieve (on another cell)
landmarks = pd.DataFrame(landmark_wid.data)[['x','y','name','color']]
'''
import holoviews as hv
from holoviews import opts, streams
from holoviews.plotting.links import DataLink
referenceplt = hv_plot_allen_regions(ccf_regions).options(
{'Curve': {
'color': 'black',
'width': 600
}})
points = hv.Points(landmarks, vdims='color').opts(marker='+', size=msize)
point_stream = streams.PointDraw(data=points.columns(),
add=False,
num_objects=4,
source=points,
empty_value='black')
table = hv.Table(points, ['x', 'y', 'name'],
'color').opts(title='Landmarks location')
DataLink(points, table)
widget = (referenceplt * points + table).opts(
opts.Layout(merge_tools=False),
opts.Points(invert_yaxis=True,
active_tools=['point_draw'],
color='color',
height=500,
tools=['hover'],
width=500), opts.Table(editable=True))
return widget, point_stream
def LoadAndCrop(video_dict,stretch={'width':1,'height':1},cropmethod='none'):
#if batch processing, set file to first file to be processed
if 'file' not in video_dict.keys():
video_dict['file'] = video_dict['FileNames'][0]
print(video_dict['file'])
#Upoad file and check that it exists
video_dict['fpath'] = os.path.join(os.path.normpath(video_dict['dpath']), video_dict['file'])
if os.path.isfile(video_dict['fpath']):
print('file: {file}'.format(file=video_dict['fpath']))
cap = cv2.VideoCapture(video_dict['fpath'])
else:
raise FileNotFoundError('{file} not found. Check that directory and file names are correct'.format(
file=video_dict['fpath']))
#Get maxiumum frame of file. Note that max frame is updated later if fewer frames detected
cap_max = int(cap.get(7)) #7 is index of total frames
print('total frames: {frames}'.format(frames=cap_max))
#Set first frame
cap.set(1,video_dict['start']) #first index references frame property, second specifies next frame to grab
ret, frame = cap.read()
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cap.release()
print('dimensions: {x}'.format(x=frame.shape))
#Make first image reference frame on which cropping can be performed
image = hv.Image((np.arange(frame.shape[1]), np.arange(frame.shape[0]), frame))
image.opts(width=int(frame.shape[1]*stretch['width']),
height=int(frame.shape[0]*stretch['height']),
invert_yaxis=True,cmap='gray',
colorbar=True,
toolbar='below',
title="First Frame. Crop if Desired")
#Create polygon element on which to draw and connect via stream to poly drawing tool
if cropmethod=='none':
image.opts(title="First Frame")
return image,None,video_dict
if cropmethod=='Box':
box = hv.Polygons([])
box.opts(alpha=.5)
box_stream = streams.BoxEdit(source=box,num_objects=1)
return (image*box),box_stream,video_dict
if cropmethod=='HLine':
points = hv.Points([])
points.opts(active_tools=['point_draw'], color='white',size=1)
pointerXY_stream = streams.PointerXY(x=0, y=0, source=image)
pointDraw_stream = streams.PointDraw(source=points,num_objects=1)
def h_track(x, y): #function to track pointer
y = int(np.around(y))
text = hv.Text(x, y, str(y), halign='left', valign='bottom')
return hv.HLine(y) * text
track=hv.DynamicMap(h_track, streams=[pointerXY_stream])
def h_line(data): #function to draw line
try:
hline=hv.HLine(data['y'][0])
return hline
except:
hline=hv.HLine(0)
return hline
line=hv.DynamicMap(h_line,streams=[pointDraw_stream])
def h_text(data): #function to write ycrop value
center=frame.shape[1]//2
try:
y=int(np.around(data['y'][0]))
htext=hv.Text(center,y+10,'ycrop: {x}'.format(x=y))
return htext
except:
htext=hv.Text(center,10, 'ycrop: 0')
return htext
text=hv.DynamicMap(h_text,streams=[pointDraw_stream])
return image*track*points*line*text,pointDraw_stream,video_dict
def LoadAndCrop(dpath, file, stretch_w=1, stretch_h=1, cropmethod='none'):
#Upoad file and check that it exists
fpath = dpath + "/" + file
if os.path.isfile(fpath):
print('file: ' + fpath)
cap = cv2.VideoCapture(fpath)
else:
raise FileNotFoundError(
'File not found. Check that directory and file names are correct.')
#Get maxiumum frame of file. Note that max frame is updated later if fewer frames detected
cap_max = int(cap.get(7)) #7 is index of total frames
print('total frames: ' + str(cap_max))
#Retrieve first frame
cap.set(
1, 0
) #first index references frame property, second specifies next frame to grab
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cap.release()
#Make first image reference frame on which cropping can be performed
image = hv.Image(
(np.arange(gray.shape[1]), np.arange(gray.shape[0]), gray))
image.opts(width=int(gray.shape[1] * stretch_w),
height=int(gray.shape[0] * stretch_h),
invert_yaxis=True,
cmap='gray',
colorbar=True,
toolbar='below',
title="First Frame. Crop if Desired")
#Create polygon element on which to draw and connect via stream to poly drawing tool
if cropmethod == 'none':
image.opts(title="First Frame")
return image, None, fpath
if cropmethod == 'Box':
box = hv.Polygons([])
box.opts(alpha=.5)
box_stream = streams.BoxEdit(source=box, num_objects=1)
return (image * box), box_stream, fpath
if cropmethod == 'HLine':
points = hv.Points([])
points.opts(active_tools=['point_draw'], color='white', size=1)
pointerXY_stream = streams.PointerXY(x=0, y=0, source=image)
pointDraw_stream = streams.PointDraw(source=points, num_objects=1)
def h_track(x, y): #function to track pointer
y = int(np.around(y))
text = hv.Text(x, y, str(y), halign='left', valign='bottom')
return hv.HLine(y) * text
track = hv.DynamicMap(h_track, streams=[pointerXY_stream])
def h_line(data): #function to draw line
try:
hline = hv.HLine(data['y'][0])
return hline
except:
hline = hv.HLine(0)
return hline
line = hv.DynamicMap(h_line, streams=[pointDraw_stream])
def h_text(data): #function to write ycrop value
center = gray.shape[1] // 2
try:
y = int(np.around(data['y'][0]))
htext = hv.Text(center, y + 10, 'ycrop: {x}'.format(x=y))
return htext
except:
htext = hv.Text(center, 10, 'ycrop: 0')
return htext
text = hv.DynamicMap(h_text, streams=[pointDraw_stream])
return image * track * points * line * text, pointDraw_stream, fpath