def test_rect_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = RectangleTool(viewer, maxdist=10)
tool.extents = (100, 150, 100, 150)
assert_equal(tool.corners,
((100, 150, 150, 100), (100, 100, 150, 150)))
assert_equal(tool.extents, (100, 150, 100, 150))
assert_equal(tool.edge_centers,
((100, 125.0, 150, 125.0), (125.0, 100, 125.0, 150)))
assert_equal(tool.geometry, (100, 150, 100, 150))
# grab a corner and move it
do_event(viewer, 'mouse_press', xdata=100, ydata=100)
do_event(viewer, 'move', xdata=120, ydata=120)
do_event(viewer, 'mouse_release')
# assert_equal(tool.geometry, [120, 150, 120, 150])
# create a new line
do_event(viewer, 'mouse_press', xdata=10, ydata=10)
do_event(viewer, 'move', xdata=100, ydata=100)
do_event(viewer, 'mouse_release')
assert_equal(tool.geometry, [10, 100, 10, 100])
def test_rect_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = RectangleTool(viewer, maxdist=10)
tool.extents = (100, 150, 100, 150)
assert_equal(tool.corners,
((100, 150, 150, 100), (100, 100, 150, 150)))
assert_equal(tool.extents, (100, 150, 100, 150))
assert_equal(tool.edge_centers,
((100, 125.0, 150, 125.0), (125.0, 100, 125.0, 150)))
assert_equal(tool.geometry, (100, 150, 100, 150))
# grab a corner and move it
do_event(viewer, 'mouse_press', xdata=100, ydata=100)
do_event(viewer, 'move', xdata=120, ydata=120)
do_event(viewer, 'mouse_release')
# assert_equal(tool.geometry, [120, 150, 120, 150])
# create a new line
do_event(viewer, 'mouse_press', xdata=10, ydata=10)
do_event(viewer, 'move', xdata=100, ydata=100)
do_event(viewer, 'mouse_release')
assert_equal(tool.geometry, [10, 100, 10, 100])
def attach(self, image_viewer):
super(TilePreview, self).attach(image_viewer)
self.rect_tool = RectangleTool(self.image_viewer,
on_release=self.update)
self.ax.set_xticks(())
self.ax.set_yticks(())
self.ax.autoscale_view('tight')
def get_ROI(im):
global viewer,coord_list,selecting
selecting=True
finished=False
while selecting:
viewer = ImageViewer(im)
coord_list = []
rect_tool = RectangleTool(viewer, on_enter=get_rect_coord)
viewer.show()
return coord_list
def get_ROI(im):
global viewer, coord_list
selecting = True
while selecting:
viewer = ImageViewer(im)
coord_list = []
rect_tool = RectangleTool(viewer, on_enter=get_rect_coord)
print "Draw your selections, press ENTER to validate one and close the window when you are finished"
viewer.show()
finished = raw_input('Is the selection correct? [y]/n: ')
if finished != 'n':
selecting = False
return coord_list
def selectRoi(img, message='Select Region of Interest', roi=None):
from skimage.viewer import ImageViewer
from skimage.viewer.canvastools import RectangleTool
if roi is None:
roi = Roi()
viewer = ImageViewer(img)
viewer.fig.suptitle(message)
rect = RectangleTool(viewer)
viewer.show()
extents = np.round(rect.extents).astype('int64')
roi.x_start = extents[0]
roi.x_end = extents[1]
roi.y_start = extents[2]
roi.y_end = extents[3]
return roi
def draw_rectangle(self):
"""Draw a rectangle on the image and return the coordinates
Returns
-------
box: ndarray
[xmin,xmax,ymin,ymax]"""
viewer=ImageViewer(self)
viewer.show()
from skimage.viewer.canvastools import RectangleTool
rect_selected_yet={'done':False} #mutable object to store func status in
rect_tool = RectangleTool(viewer, on_enter=_rect_selected)
while not rect_selected_yet['done']:
time.sleep(2)
pass
coords=np.int64(rect_tool.extents)
viewer.close()
return coords
def remove_object_loop(img):
print("Remove object")
viewer = ImageViewer(img)
def on_enter(extens):
coord = np.int64(extens)
[x0, y0] = [coord[2], coord[0]]
[x1, y1] = [coord[3], coord[1]]
print([x0, y0], [x1, y1])
(x, y) = (x0, y0)
(len_x, len_y) = (x1 - x, y1 - y)
viewer.image = remove_object(viewer.image, x0, y0, len_x, len_y)
rect_tool = RectangleTool(viewer, on_enter=on_enter)
viewer.show()
return viewer.image
def get_crop(image):
'''
Show the original image to allow the user to crop any extraneous
information out of the frame.
:param image: 2D numpy array grayscale image
:return: list of [left, right, top, bottom] values for the edges of the
bounding box
'''
plt.ioff()
print('Waiting for input, please crop the image as desired and hit enter')
viewer = ImageViewer(image)
rect_tool = RectangleTool(viewer, on_enter=viewer.closeEvent)
viewer.show()
bounds = np.array(rect_tool.extents)
if (bounds[0] < 0 or bounds[1] > image.shape[1] or bounds[2] < 0
or bounds[3] > image.shape[0]):
print(f'Bounds = {bounds} and shape = {image.shape}')
raise ValueError('Bounds outside image, make sure to select within')
plt.ion()
return np.array(np.round(bounds), dtype=int)
def test_rect_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = RectangleTool(viewer.ax, maxdist=10)
tool.extents = (100, 150, 100, 150)
assert_equal(tool.corners,
((100, 150, 150, 100), (100, 100, 150, 150)))
assert_equal(tool.extents, (100, 150, 100, 150))
assert_equal(tool.edge_centers,
((100, 125.0, 150, 125.0), (125.0, 100, 125.0, 150)))
assert_equal(tool.geometry, (100, 150, 100, 150))
# grab a corner and move it
grab = create_mouse_event(viewer.ax, xdata=100, ydata=100)
tool.press(grab)
move = create_mouse_event(viewer.ax, xdata=120, ydata=120)
tool.onmove(move)
tool.release(move)
assert_equal(tool.geometry, [120, 150, 120, 150])
# create a new line
new = create_mouse_event(viewer.ax, xdata=10, ydata=10)
tool.press(new)
move = create_mouse_event(viewer.ax, xdata=100, ydata=100)
tool.onmove(move)
tool.release(move)
assert_equal(tool.geometry, [10, 100, 10, 100])
conversion = np.array([0.2125, 0.7154, 0.0721])
#Perform the conversion and extract only so many frames to analyze
images = [
np.dot(im, conversion) for i, im in enumerate(images)
if ((i / np.round(fps) - startSeconds) %
everyNSeconds) == 0 and (i / np.round(fps) > startSeconds)
]
images = [im / im.max() for im in images]
# Get 4-list of points for left, right, top, and bottom crop (in that order)
# Show the first image in the stack so that user can select crop box
print('Waiting for your input, please crop the image as desired and hit enter')
viewer = ImageViewer(images[0])
rect_tool = RectangleTool(viewer, on_enter=viewer.closeEvent)
viewer.show()
cropPoints = np.array(rect_tool.extents)
cropPoints = np.array(np.round(cropPoints), dtype=int)
time = []
angles = []
volumes = []
baselineWidth = []
# Make sure that the edges are being detected well
edges = feature.canny(images[0], sigma=σ)
fig, ax = plt.subplots(2,
1,
gridspec_kw={'height_ratios': [10, 1]},
figsize=(8, 8))
image = io.imread(filename[framenr])
return image
filetypes = {0: movie, 1: tifstack, 2: images}
image = filetypes[filetype]()
return image
image = getcurrframe(filename, 0, filetype)
#preallocate crop coordinates, maybe unescecarry?
coords = [0, 0, 0, 0]
#show the image and ask for a crop from the user, using skimage.viewer canvastools
viewer = ImageViewer(image)
rect_tool = RectangleTool(
viewer, on_enter=viewer.closeEvent) #actually call the imageviewer
viewer.show() #don't forget to show it
coords = np.array(rect_tool.extents)
coords = np.array(np.around(coords), dtype=int)
#crop the image
cropped = image[coords[2]:coords[3], coords[0]:coords[1]]
framesize = cropped.shape
baseinput = np.array([0, 0, 0, 0])
#userinput for the baseline, on which we'll find the contact angles, using skimage.viewer
viewer = ImageViewer(cropped)
line_tool = LineTool(viewer, on_enter=viewer.closeEvent)
viewer.show()
baseinput = line_tool.end_points
#extend the baseline to the edge of the frame (in case the drop grows)
def test_rect_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = RectangleTool(viewer.ax, maxdist=10)
tool.extents = (100, 150, 100, 150)
assert_equal(tool.corners, ((100, 150, 150, 100), (100, 100, 150, 150)))
assert_equal(tool.extents, (100, 150, 100, 150))
assert_equal(tool.edge_centers,
((100, 125.0, 150, 125.0), (125.0, 100, 125.0, 150)))
assert_equal(tool.geometry, (100, 150, 100, 150))
# grab a corner and move it
grab = create_mouse_event(viewer.ax, xdata=100, ydata=100)
tool.press(grab)
move = create_mouse_event(viewer.ax, xdata=120, ydata=120)
tool.onmove(move)
tool.release(move)
assert_equal(tool.geometry, [120, 150, 120, 150])
# create a new line
new = create_mouse_event(viewer.ax, xdata=10, ydata=10)
tool.press(new)
move = create_mouse_event(viewer.ax, xdata=100, ydata=100)
tool.onmove(move)
tool.release(move)
assert_equal(tool.geometry, [10, 100, 10, 100])
def main():
algorithms = {
'dynamicprogramming': get_best_column_dynamicprogramming,
'greedy': get_best_column_greedy,
'random': get_best_column_random
}
default_algorithm = 'dynamicprogramming'
parser = argparse.ArgumentParser(
description='Content aware image resizing using seam carving.')
parser.add_argument('source',
type=str,
help='Input picture to be resized.')
parser.add_argument('output',
type=str,
help='Output with the resized picture.')
parser.add_argument('--width', type=int, help='Change in width.')
parser.add_argument('--height', type=int, help='Change in height.')
parser.add_argument(
'--amplify-content',
type=float,
help='Amplify content with a desired factor.' +
'For example, use 1.2 to amplify the content with 20%.')
parser.add_argument('--remove-rectangle',
action='store_true',
help='Select rectangle objects to be removed.')
parser.add_argument('--algorithm',
type=str,
default=default_algorithm,
choices=algorithms.keys(),
help='Strategy to be used for seam selection.')
parser.add_argument(
'--plot-result',
action='store_true',
help='Plots the original image and the resized one side by side')
parser.add_argument(
'--plot-seam',
action='store_true',
help='Select a color in RGB format and plots the seam at each step.')
args = parser.parse_args()
img = io.imread(args.source)
original_image = img
global get_best_column
get_best_column = algorithms.get(args.algorithm, default_algorithm)
global plot_seam
global seam_color
plot_seam = args.plot_seam
seam_color = (255, 0, 0)
if args.remove_rectangle:
global viewer
viewer = ImageViewer(img)
global obj_coord
obj_coord = []
rect_tool = RectangleTool(viewer, on_enter=get_coord)
viewer.show()
img = remove_object(img, obj_coord)
if args.width:
if args.width < 0:
img = remove_column(img, -args.width)
else:
img = add_columns(img, args.width)
if args.height:
if args.height < 0:
img = remove_lines(img, -args.height)
else:
img = add_lines(img, args.height)
io.imsave(args.output, img)
if args.plot_result:
fig = plt.figure(figsize=(1, 2))
fig.add_subplot(1, 2, 1)
plt.imshow(original_image)
fig.add_subplot(
1,
2,
2,
)
plt.imshow(img)
plt.show()
def analysis(faster_fit,k,II):
import matplotlib.pyplot as plt
import numpy as np
import imageio
import os
if faster_fit:
from edge_detection import linear_subpixel_detection as edge
else:
from edge_detection import errorfunction_subpixel_detection as edge
from skimage.viewer.canvastools import RectangleTool
from skimage.viewer.canvastools import LineTool
from skimage.viewer import ImageViewer
from skimage import io
from shapely.geometry import LineString
import tkinter as tk
from tkinter import filedialog
PO=3 #polyfit order for edge fitting to measure contact angle
thresh=70 #replace with automatic treshold detection at some point
#userinput for file
root = tk.Tk()
root.withdraw()
filename = filedialog.askopenfilename()
filext=os.path.splitext(filename)[1]
#check the file type
if filename.lower().endswith('.avi') or filename.lower().endswith('.mp4'):
filetype=0
global vid
vid = imageio.get_reader(filename,)
nframes = vid.get_meta_data()['nframes']
elif filename.lower().endswith(('.tiff', '.tif')):
tiffinfo=io.MultiImage(filename)
if len(tiffinfo)>1:
filetype=1
nframes=len(tiffinfo)
else:
import glob
filetype=2
filename=glob.glob(os.path.split(filename)[0]+os.sep+'*'+filext)
filename.sort()
nframes=len(filename)
elif filename.lower().endswith(('.png', '.jpg', '.jpeg')):
import glob
filetype=2
filename=glob.glob(os.path.split(filename)[0]+os.sep+'*'+filext)
filename.sort()
nframes=len(filename)
else:
print('unknown filetype')
#function to read a specific frame from the movie, stack, or image sequence
def getcurrframe(filename,framenr,filetype):
def movie():
image=vid.get_data(framenr)[:,:,0]
return image
def tifstack():
stack=io.imread(filename)
image=stack[framenr,:,:]
return image
def images():
image=io.imread(filename[framenr])
return image
filetypes={0 : movie,
1 : tifstack,
2 : images
}
image=filetypes[filetype]()
return image
image = getcurrframe(filename,0,filetype)
#preallocate crop coordinates, maybe unescecarry?
coords=[0,0,0,0]
#show the image and ask for a crop from the user, using skimage.viewer canvastools
viewer = ImageViewer(image)
rect_tool = RectangleTool(viewer, on_enter=viewer.closeEvent) #actually call the imageviewer
viewer.show() #don't forget to show it
coords=np.array(rect_tool.extents)
coords=np.array(np.around(coords),dtype=int)
#crop the image
cropped=image[coords[2]:coords[3],coords[0]:coords[1]]
framesize=cropped.shape
baseinput=np.array([0,0,0,0])
#userinput for the baseline, on which we'll find the contact angles, using skimage.viewer
viewer = ImageViewer(cropped)
line_tool=LineTool(viewer,on_enter=viewer.closeEvent)
viewer.show()
baseinput=line_tool.end_points
#extend the baseline to the edge of the frame (in case the drop grows)
rightbasepoint=np.argmax([baseinput[0,0],baseinput[1,0]])
baseslope=np.float(baseinput[rightbasepoint,1]-baseinput[1-rightbasepoint,1])/(baseinput[rightbasepoint,0]-baseinput[1-rightbasepoint,0])
base=np.array([[0,baseinput[0,1]-baseslope*baseinput[0,0]],[framesize[1],baseslope*framesize[1]+baseinput[0,1]-baseslope*baseinput[0,0]]])
#preallocation of edges, angles and contact points
edgeleft=np.zeros(framesize[0])
edgeright=np.zeros(framesize[0])
thetal=np.zeros(nframes)
thetar=np.zeros(nframes)
contactpointright=np.zeros(nframes)
contactpointleft=np.zeros(nframes)
dropvolume=np.zeros(nframes)
plt.ion()
#loop over frames
for framenr in range (nframes):
image = getcurrframe(filename,framenr,filetype) #get current frame
cropped=np.array(image[round(coords[2]):round(coords[3]),round(coords[0]):round(coords[1])]) #crop frame
edgeleft, edgeright=edge(cropped,thresh) #find the edge with edge function in edge_detection.py
baseline=LineString(base) #using shapely we construct baseline
rightline=LineString(np.column_stack((edgeright,(range(0,framesize[0]))))) #and the lines of the edges
leftline=LineString(np.column_stack((edgeleft,(range(0,framesize[0])))))
leftcontact=baseline.intersection(leftline) #we find the intersectionpoint of the baseline with the edge
rightcontact=baseline.intersection(rightline)
#Detect small drops that are lower than 'k' pixels
#This may break if the drop grows outside the frame on one side. Maybe fix later?
fitpointsleft=edgeleft[range(np.int(np.floor(leftcontact.y)),np.int(np.floor(leftcontact.y)-k),-1)]
if any(fitpointsleft==0):
fitpointsleft=np.delete(fitpointsleft,range(np.argmax(fitpointsleft==0),k))
#polyfit the edges around the baseline, but flipped, because polyfitting a vertical line is bad
leftfit=np.polyfit(range(0,fitpointsleft.shape[0]),fitpointsleft,PO)
leftvec=np.array([1,leftfit[PO-1]]) #vector for angle calculation
fitpointsright=edgeright[range(np.int(np.floor(leftcontact.y)),np.int(np.floor(leftcontact.y)-k),-1)]
if any(fitpointsright==0):
fitpointsright=np.delete(fitpointsright,range(np.argmax(fitpointsright==0),k))
#polyfit the edges around the baseline, but flipped, because polyfitting a vertical line is bad
rightfit=np.polyfit(range(0,fitpointsright.shape[0]),fitpointsright,PO)
rightvec=np.array([1,rightfit[PO-1]]) #vector for angle calculation
basevec=np.array([-baseslope,1]) #base vector for angle calculation (allows for a sloped basline if the camera was tilted)
#calculate the angles using the dot product.
thetal[framenr]=np.arccos(np.dot(basevec,leftvec)/(np.sqrt(np.dot(basevec,basevec))*np.sqrt(np.dot(leftvec,leftvec))))*180/np.pi
thetar[framenr]=180-np.arccos(np.dot(basevec,rightvec)/(np.sqrt(np.dot(basevec,basevec))*np.sqrt(np.dot(rightvec,rightvec))))*180/np.pi
if framenr % II ==0: #plot every II frames, to get a visual indication of how far along the script is
plt.clf()
plt.imshow(image[round(coords[2]):round(coords[3]),round(coords[0]):round(coords[1])],cmap='gray',interpolation="nearest")
plt.plot(edgeleft,range(0,framesize[0]))
plt.plot(edgeright,range(0,framesize[0]))
plt.plot([base[0,0],base[1,0]],[base[0,1],base[1,1]])
plt.title('frame %d of %d' % (framenr, nframes))
plt.pause(0.001)
#save the contact point (the point where the polyfit intersects the baseline)
contactpointright[framenr]=rightfit[PO]
contactpointleft[framenr]=leftfit[PO]
for height in range (0,min(np.int(np.floor(leftcontact.y)),np.int(np.floor(rightcontact.y)))):
dropvolume[framenr]=dropvolume[framenr]+np.pi*np.square((edgeright[height]-edgeleft[height])/2) #volume of each slice in pixels^3, without taking a possible slanted baseline into account
#using cylindrical slice we calculate the remaining volume
slantedbasediff=max(np.floor(leftcontact.y),np.floor(rightcontact.y))-min(np.floor(leftcontact.y),np.floor(rightcontact.y))
#we assume that the radius is constant over the range of the slanted baseline, for small angles this is probably accurate, but for larger angles this is probably wrong.
baseradius=(edgeright[np.int(min(np.floor(leftcontact.y),np.floor(rightcontact.y)))]-edgeleft[np.int(min(np.floor(leftcontact.y),np.floor(rightcontact.y)))])/2
dropvolume[framenr]=dropvolume[framenr]+.5*np.pi*np.square(baseradius)*slantedbasediff
#%%
fitsamplesize=3
if nframes>2*fitsamplesize+1:
leftspeed=np.zeros(nframes)
rightspeed=np.zeros(nframes)
for framenr in range(fitsamplesize,nframes-fitsamplesize-1):
rightposfit=np.polyfit(range(-fitsamplesize,fitsamplesize),contactpointright[range(framenr-fitsamplesize,framenr+fitsamplesize)],1)
leftposfit=np.polyfit(range(-fitsamplesize,fitsamplesize),contactpointleft[range(framenr-fitsamplesize,framenr+fitsamplesize)],1)
leftspeed[framenr]=leftposfit[0]
rightspeed[framenr]=rightposfit[0]
for fillinrest in range(0,fitsamplesize):
leftspeed[fillinrest]=leftspeed[fitsamplesize]
rightspeed[fillinrest]=rightspeed[fitsamplesize]
for fillinrest in range(nframes-fitsamplesize-1,nframes-1):
leftspeed[fillinrest]=leftspeed[nframes-fitsamplesize-1]
rightspeed[fillinrest]=rightspeed[nframes-fitsamplesize-1]
plt.close() #close the plot after we're done
elif nframes>1:
for framenr in range(0,nframes-2):
leftspeed[framenr]=contactpointleft[framenr+1]-contactpointleft[framenr]
rightspeed[framenr]=contactpointright[framenr+1]-contactpointright[framenr]
rightspeed[framenr-1]=rightspeed[framenr-2]
leftspeed[framenr-1]=leftspeed[framenr-2]
else:
leftspeed=0
rightspeed=0
return thetal, thetar, leftspeed, rightspeed, contactpointleft, contactpointright, dropvolume;
