mesher = dic.Mesher(deg_e=3, deg_n=3) # mesh = mesher.mesh(images,Xc1=200,Xc2=1050,Yc1=200,Yc2=650,n_ely=8,n_elx=8, GUI=True) mesh = mesher.mesh(images, Xc1=20, Xc2=105, Yc1=20, Yc2=65, n_ely=8, n_elx=8, GUI=True) # Instantiate settings object and set some settings manually settings = dic.DICInput(mesh, images) # 图像数量 settings.max_nr_im = 2 settings.ref_update = [15] settings.maxit = 20 # If you want to access the residual fields after the analysis, this should be set to True settings.store_internals = False # Instantiate job object job = dic.DICAnalysis(settings) # Running DIC analysis dic_results = job.run() # 用于仿真，假设z均为3,拼接出三维obj_points # 世界三维坐标为参考图的点 cols, rows = dic_results.xnodesT.shape obj_points = np.zeros((cols, 3), np.float32) obj_points[:, 0] = dic_results.xnodesT[:, 0] obj_points[:, 1] = dic_results.ynodesT[:, 0] # obj_points = np.append(np.array(dic_results.xnodesT[:, 1]), np.array(dic_results.ynodesT[:, 1])) znodes = np.zeros(cols, np.float32) # obj_points = np.append(obj_points, znodes, axis=1) obj_points[:, 2] = znodes objectpoints = []
mesher = dic.Mesher(deg_n=3, deg_e=3, type="spline")
#mesh = mesher.mesh(image_stack) # Use this if you want to mesh with a GUI
mesh = mesher.mesh(image_stack,
Xc1=50,
Xc2=450,
Yc1=50,
Yc2=450,
n_ely=8,
n_elx=8,
GUI=False)
# Prepare the analysis input and initiate the analysis
input = dic.DICInput(mesh, image_stack)
input.tol = 1e-6
dic_job = dic.DICAnalysis(input)
results = dic_job.run()
# Calculate the fields for later use
fields = dic.Fields(results, seed=101)
# We will now compare the results from the analysis to the displacement which the image was deformed by
# We do this by evaluating the same function as used to deform the images.
# First we find the image coordinates of the image
xs, ys = dic.utils.image_coordinates(image_stack[0])
# We then find the displacement components for each image coordinate
u_x, u_y = displacement_function(xs, ys, omega=2. * np.pi / 500., amp=2.0)
# We now need to find the material points used in the DIC analysis, and extract the corresponding
# correct displacement values
def run_DIC(folder_path, n_images, filter, filter_sigma, maxim, maxit, padding,
poly_order, converge):
# Set the amount of info printed to terminal during analysis
logging.basicConfig(format='%(name)s:%(levelname)s:%(message)s',
level=logging.INFO)
# Path to folder containing images
path = folder_path
# Generate image instance containing all images found in the folder
images = dic.IO.image_stack_from_folder(path, file_type='.png')
images.use_every_n_image(int(n_images))
if filter == "Lowpass Gaussian":
images.set_filter(dic.filtering.lowpass_gaussian,
sigma=int(filter_sigma))
elif filter == "Highpass Gaussian":
images.set_filter(dic.filtering.highpass_gaussian,
sigma=int(filter_sigma))
elif filter == "Homomorphic Median":
images.set_filter(dic.filtering.homomorphic_median,
sigma=int(filter_sigma))
else:
pass
# Generate mesh
mesher = dic.Mesher(deg_e=3, deg_n=3, type="q4") #type="b_splines")
mesh = mesher.mesh(images,
Xc1=316,
Xc2=523,
Yc1=209,
Yc2=1055,
n_ely=18,
n_elx=5,
GUI=True)
# Instantiate settings object and set some settings manually (first video)
settings = dic.DICInput(mesh, images)
if bool(maxim):
settings.max_nr_im = int(maxim)
settings.ref_update = [15]
settings.maxit = int(maxit)
settings.tol = 1.e-6
settings.interpolation_order = int(poly_order)
# If you want to access the residual fields after the analysis, this should be set to True
settings.store_internals = True
# This setting defines the behaviour when convergence is not obtained
if converge == "Ignore":
settings.noconvergence = "ignore"
elif converge == "Update":
settings.noconvergence = "update"
elif converge == "Break":
settings.noconvergence = "break"
else:
pass
# Instantiate job object
job = dic.DICAnalysis(settings)
# Running DIC analysis
dic_results = job.run()
return images, dic_results
