In [1]:
# %load red_Cell.py
from openpiv import tools, pyprocess, scaling, filters, \
validation, process
import numpy as np
from skimage import data
import matplotlib.pyplot as plt
from scipy import ndimage
from skimage import feature
from PIL import Image
from pylab import *
%matplotlib inline
from skimage.color import rgb2gray
from skimage import img_as_uint
frame_a = tools.imread('../test3/Y4-S3_Camera000398.tif')
frame_b = tools.imread('../test3/Y4-S3_Camera000399.tif')
# for whatever reason the shape of frame_a is (3, 284, 256)
# so we first tranpose to the RGB image and then convert to the gray scale
frame_a = img_as_uint(rgb2gray(frame_a))
frame_b = img_as_uint(rgb2gray(frame_b))
plt.imshow(np.c_[frame_a,frame_b],cmap=plt.cm.gray)
/Users/alex/miniconda3/envs/openpiv3/lib/python3.7/site-packages/skimage/util/dtype.py:135: UserWarning: Possible precision loss when converting from float64 to uint16 .format(dtypeobj_in, dtypeobj_out))
Out[1]:
<matplotlib.image.AxesImage at 0x127d2c6d8>
In [2]:
# frame_a.dtype
In [3]:
#u, v, sig2noise = openpiv.process.extended_search_area_piv( frame_a, frame_b, window_size=24, overlap=12, dt=0.02, search_area_size=64, sig2noise_method='peak2peak' )
u, v, sig2noise = pyprocess.extended_search_area_piv( frame_a, frame_b, window_size=32, overlap=8, dt=.1, sig2noise_method='peak2peak' )
x, y = pyprocess.get_coordinates( image_size=frame_a.shape, window_size=32, overlap=8 )
In [4]:
u, v, mask = validation.sig2noise_val( u, v, sig2noise, threshold = 1.3 )
u, v = filters.replace_outliers( u, v, method='localmean', max_iter=10, kernel_size=2)
x, y, u, v = scaling.uniform(x, y, u, v, scaling_factor = 96.52 )
quiver(x,y,u,v)
Out[4]:
<matplotlib.quiver.Quiver at 0x1092b92b0>
In [5]:
tools.save(x, y, u, v, mask, 'Y4-S3_Camera000398.txt' )
tools.display_vector_field('Y4-S3_Camera000398.txt', scale=3, width=0.0125)
# frame_vectors = io.imshow(vectors)
In [6]:
x,y,u,v, mask = process.WiDIM(frame_a.astype(np.int32), frame_b.astype(np.int32), ones_like(frame_a).astype(np.int32), min_window_size=32, overlap_ratio=0.25, coarse_factor=0, dt=0.1, validation_method='mean_velocity', trust_1st_iter=0, validation_iter=0, tolerance=0.7, nb_iter_max=1, sig2noise_method='peak2peak')
----------------------------------------------------------
|-----> || The Open Source P article |
| Open || I mage |
| PIV || V elocimetry Toolbox |
| <-----|| www.openpiv.net version 1.0 |
----------------------------------------------------------
('Algorithm : ', 'WiDIM')
Parameters
-----------------------------------
(' ', 'Size of image', ' | ', [284, 256])
(' ', 'total number of iterations', ' | ', 1)
(' ', 'overlap ratio', ' | ', 0.25)
(' ', 'coarse factor', ' | ', 0)
(' ', 'time step', ' | ', 0.10000000149011612)
(' ', 'validation method', ' | ', 'None')
(' ', 'number of validation iterations', ' | ', 0)
(' ', 'subpixel_method', ' | ', 'gaussian')
(' ', 'Nrow', ' | ', array([11], dtype=int32))
(' ', 'Ncol', ' | ', array([10], dtype=int32))
(' ', 'Window sizes', ' | ', array([32], dtype=int32))
-----------------------------------
| STARTING |
-----------------------------------
('ITERATION # ', 0)
..[DONE]
(' --residual : ', 1.000000045849729)
Starting validation..
..[DONE]
//////////////////////////////////////////////////////////////////
end of iterative process.. Re-arranging vector fields..
...[DONE]
-------------------------------------------------------------
('[DONE] ..after ', 21.504817962646484, 'seconds ')
-------------------------------------------------------------
In [7]:
tools.save(x, y, u, v, zeros_like(u), 'Y4-S3_Camera000398.txt' )
tools.display_vector_field('Y4-S3_Camera000398.txt', scale=300, width=0.005)
In [8]:
x,y,u,v, mask = process.WiDIM(frame_a.astype(np.int32), frame_b.astype(np.int32), ones_like(frame_a).astype(np.int32), min_window_size=16, overlap_ratio=0.25, coarse_factor=2, dt=0.1, validation_method='mean_velocity', trust_1st_iter=1, validation_iter=2, tolerance=0.7, nb_iter_max=4, sig2noise_method='peak2peak')
----------------------------------------------------------
|-----> || The Open Source P article |
| Open || I mage |
| PIV || V elocimetry Toolbox |
| <-----|| www.openpiv.net version 1.0 |
----------------------------------------------------------
('Algorithm : ', 'WiDIM')
Parameters
-----------------------------------
(' ', 'Size of image', ' | ', [284, 256])
(' ', 'total number of iterations', ' | ', 4)
(' ', 'overlap ratio', ' | ', 0.25)
(' ', 'coarse factor', ' | ', 2)
(' ', 'time step', ' | ', 0.10000000149011612)
(' ', 'validation method', ' | ', 'mean_velocity')
(' ', 'number of validation iterations', ' | ', 2)
(' ', 'subpixel_method', ' | ', 'gaussian')
(' ', 'Nrow', ' | ', array([ 5, 11, 23, 23], dtype=int32))
(' ', 'Ncol', ' | ', array([ 5, 10, 21, 21], dtype=int32))
(' ', 'Window sizes', ' | ', array([64, 32, 16, 16], dtype=int32))
-----------------------------------
| STARTING |
-----------------------------------
('ITERATION # ', 0)
..[DONE]
(' --residual : ', 1.0000000125483464)
no validation : trusting 1st iteration
going to next iteration..
performing interpolation of the displacement field
('..[DONE] -----> going to iteration ', 1)
('ITERATION # ', 1)
..[DONE]
(' --residual : ', 0.22727273012462418)
Starting validation..
('Validation, iteration number ', 0)
('Validation, iteration number ', 1)
..[DONE]
going to next iteration..
performing interpolation of the displacement field
('..[DONE] -----> going to iteration ', 2)
('ITERATION # ', 2)
..[DONE]
(' --residual : ', 0.6429116349607981)
Starting validation..
('Validation, iteration number ', 0)
('Validation, iteration number ', 1)
..[DONE]
going to next iteration..
performing interpolation of the displacement field
('..[DONE] -----> going to iteration ', 3)
('ITERATION # ', 3)
..[DONE]
(' --residual : ', 0.629290625745527)
Starting validation..
('Validation, iteration number ', 0)
('Validation, iteration number ', 1)
..[DONE]
//////////////////////////////////////////////////////////////////
end of iterative process.. Re-arranging vector fields..
...[DONE]
-------------------------------------------------------------
('[DONE] ..after ', 22.8556649684906, 'seconds ')
-------------------------------------------------------------
In [9]:
tools.save(x, y, u, v, zeros_like(u), 'Y4-S3_Camera000398.txt' )
tools.display_vector_field('Y4-S3_Camera000398.txt', scale=300, width=0.005)
In [ ]: