from DICpy.utils import _close
import numpy as np
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import os
import skimage.io as sio
from matplotlib.widgets import Button
import cv2
[docs]class Images:
"""
This class contains the methods for reading and processing images used in digital image correlation (DIC).
**Input:**
**Attributes:**
* **path_speckle** (`str`)
Path to the speckle images.
* **path_calibration** (`str`)
Path to the calibration image.
* **ref_image** (`ndarray`)
Reference image.
* **calibration_image** (`ndarray`)
Calibration image.
* **images** (`ndarray`)
Gray images.
* **images_normalized** (`ndarray`)
Gray images normalized by 255.
* **lx** (`int`)
Number of columns of each image.
* **ly** (`int`)
Number of rows of each image.
* **num_img** (`int`)
Number of images.
* **pixel_dim** (`float`)
Size of each pixel in length dimension.
**Methods:**
"""
def __init__(self):
self.path_speckle = None
self.path_calibration = None
self.ref_image = None
self.calibration_image = None
self.images = None
self.images_normalized = None
self.lx = None
self.ly = None
self.num_img = None
self.pixel_dim = 1
[docs] def read_speckle_images(self, path=None, extension=None, file_names=None, ref_id=0, verbose=False):
"""
Read the speckle images.
**Input:**
* **path** (`str`)
Path for the images used in the DIC analysis.
* **extension** (`str`)
The extension of the files located in `path`.
* **file_names** (`str`)
Define the files to be read in the sequence of your preference.
* **ref_id** (`int`)
Define a file to be used as reference, the default is zero, which means that the first image in the stack will
be used as reference.
* **verbose** (`bool`)
Boolean varible to print some information on screen.
**Output/Returns:**
"""
if not isinstance(ref_id,int):
raise TypeError('DICpy: ref_id must be an integer.')
if ref_id < 0:
raise ValueError('DICpy: ref_id is an integer larger than or equal to 0.')
if path is None:
path = os.getcwd()
if extension is None:
raise TypeError('DICpy: extension cannot be NoneType when using path.')
self.path_speckle = path
if file_names is None:
file_names = [f for f in os.listdir(path) if f.endswith('.' + extension)]
file_names = np.sort(file_names)
if verbose:
print('DICpy: reading speckle images.')
images = []
images_normalized = []
for f in file_names:
if verbose:
print(f)
im = cv2.imread(os.path.join(path, f), 0)
images.append(im)
images_normalized.append(im/255)
self.images = images
self.images_normalized = images_normalized
(lx, ly) = np.shape(im)
self.lx = lx
self.ly = ly
self.num_img = len(images)
self.ref_image = images[ref_id]
@staticmethod
def _read_calibration_images(path=None, file_name=None, verbose=True):
"""
Private method for reading the calibration image.
**Input:**
* **path** (`str`)
Path for the calibration image used in the DIC analysis.
* **file_names** (`str`)
Name of the calibration image.
* **verbose** (`bool`)
Boolean varible to print some information on screen.
**Output/Returns:**
* **calibration_image** (`ndarray`)
Calibration image.
"""
if path is None:
path = os.getcwd()
if file_name is None:
raise TypeError('DICpy: file_name cannot be NoneType.')
if verbose:
print('DICpy: reading the calibration image.')
im = sio.imread(os.path.join(path, file_name), as_gray=True)
calibration_image = 255 * im
return calibration_image
[docs] def calibration(self, ref_length=None, pixel_dim=None, path=None, file_name=None,
point_a=None, point_b=None, verbose=True):
"""
Method for the analysis calibration.
**Input:**
* **ref_length** (`str`)
Length used as reference.
* **pixel_dim** (`float`)
Size of each pixel in length dimension.
* **path** (`str`)
Path for the calibration image used in the DIC analysis.
* **file_name** (`str`)
Name of the calibration image.
* **point_a** (`float`)
First corner of the region of interest (ROI).
* **point_b** (`float`)
Corner opposed to point_b of the region of interest (ROI).
* **verbose** (`bool`)
Boolean variable to print some information on screen.
**Output/Returns:**
"""
if pixel_dim is None:
if ref_length is None:
raise TypeError('DICpy: ref_length cannot be NoneType.')
self.path_calibration = path
cal_img = self._read_calibration_images(path=path, file_name=file_name, verbose=verbose)
self.calibration_image = cal_img
(lx, ly) = np.shape(cal_img)
maxl = max(lx, ly)
global rcirc, ax, fig, coords, cid
rcirc = maxl / 160
if point_a is None or point_b is None:
coords = []
fig = plt.figure()
ax = fig.add_subplot(111)
cid = fig.canvas.mpl_connect('button_press_event', self._mouse_click)
plt.imshow(cal_img, cmap="gray")
plt.show()
point_a = coords[0]
point_b = coords[1]
else:
fig = plt.figure()
ax = fig.add_subplot(111)
circle = plt.Circle(point_a, rcirc, color='red')
ax.add_patch(circle)
fig.canvas.draw() # this line was missing earlier
circle = plt.Circle(point_b, rcirc, color='red')
ax.add_patch(circle)
fig.canvas.draw() # this line was missing earlier
lx = (point_b[0] - point_a[0])
ly = (point_b[1] - point_a[1])
fig.canvas.draw() # this line was missing earlier
plt.imshow(cal_img, cmap="gray")
plt.show(block=False)
plt.close()
point_a = (round(point_a[0]),round(point_a[1]))
point_b = (round(point_b[0]),round(point_b[1]))
fig = plt.figure()
ax = fig.add_subplot(111)
lx = (point_b[0] - point_a[0])
ly = (point_b[1] - point_a[1])
circle = plt.Circle(point_a, rcirc, color='red')
ax.add_patch(circle)
fig.canvas.draw() # this line was missing earlier
circle = plt.Circle(point_b, rcirc, color='red')
ax.add_patch(circle)
fig.canvas.draw() # this line was missing earlier
ax.plot([point_a[0], point_b[0]], [point_a[1], point_b[1]], linewidth=2)
fig.canvas.draw()
plt.imshow(cal_img, cmap="gray")
axclose = plt.axes([0.81, 0.05, 0.1, 0.075])
bclose = Button(axclose, 'Next')
bclose.on_clicked(_close)
plt.show()
self.pixel_dim = ref_length/np.sqrt(lx**2 + ly**2)
if verbose:
print("Points: ",point_a,point_b)
print("mm/pixel: ",self.pixel_dim)
else:
if ref_length is not None:
raise Warning('DICpy: ref_length not used when pixel_dim is provided.')
self.pixel_dim = pixel_dim
if verbose:
print("mm/pixel: ",self.pixel_dim)
@staticmethod
def _mouse_click(event):
"""
Private method: mouse click to select the ROI.
**Input:**
* **event** (`event`)
Click event.
**Output/Returns:**
"""
global x, y
x, y = event.xdata, event.ydata
if event.button:
circle = plt.Circle((event.xdata, event.ydata), rcirc, color='red')
ax.add_patch(circle)
fig.canvas.draw() # this line was missing earlier
global coords
coords.append((x, y))
if len(coords) == 2:
fig.canvas.mpl_disconnect(cid)
xa = coords[0][0]
ya = coords[0][1]
xb = coords[1][0]
yb = coords[1][1]
lx = (xb - xa)
ly = (yb - ya)
rect = patches.Rectangle((xa, ya), lx, ly, linewidth=1, edgecolor='None', facecolor='b', alpha=0.4)
ax.add_patch(rect)
fig.canvas.draw() # this line was missing earlier
plt.close()
return coords
