def test_line_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = LineTool(viewer, maxdist=10)
tool.end_points = get_end_points(img)
assert_equal(tool.end_points, np.array([[170, 256], [341, 256]]))
# grab a handle and move it
do_event(viewer, 'mouse_press', xdata=170, ydata=256)
do_event(viewer, 'move', xdata=180, ydata=260)
do_event(viewer, 'mouse_release')
assert_equal(tool.geometry, np.array([[180, 260], [341, 256]]))
# 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, np.array([[100, 100], [10, 10]]))
def test_line_tool():
img = data.camera()
viewer = ImageViewer(img)
tool = LineTool(viewer.ax, maxdist=10)
tool.end_points = get_end_points(img)
assert_equal(tool.end_points, np.array([[170, 256], [341, 256]]))
# grab a handle and move it
grab = create_mouse_event(viewer.ax, xdata=170, ydata=256)
tool.on_mouse_press(grab)
move = create_mouse_event(viewer.ax, xdata=180, ydata=260)
tool.on_move(move)
tool.on_mouse_release(move)
assert_equal(tool.geometry, np.array([[180, 260], [341, 256]]))
# create a new line
new = create_mouse_event(viewer.ax, xdata=10, ydata=10)
tool.on_mouse_press(new)
move = create_mouse_event(viewer.ax, xdata=100, ydata=100)
tool.on_move(move)
tool.on_mouse_release(move)
assert_equal(tool.geometry, np.array([[100, 100], [10, 10]]))
#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
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;