def check(tilt, img0, img180): """check tilt using a pair of images """ from imars3d import io apply(tilt, img0, io.ImageFile("tilted-0.npy")) apply(tilt, img180, io.ImageFile("tilted-180.npy")) return
def getEdge(imgpath, edgepath, **kwds): img = io.ImageFile(imgpath).data edge = feature.canny(img, **kwds) edge = np.array(edge, dtype="float32") edgeimg = io.ImageFile(path=edgepath) edgeimg.data = edge edgeimg.save() return edge
def _test_ext(ext): data = np.arange(300 * 400, dtype="float32") data.shape = 300, 400 imgfile = io.ImageFile("img1.%s" % ext) imgfile.data = data imgfile.save() data2 = io.ImageFile("img1.%s" % ext).data assert ((data == data2).all()) return
def main(): img0 = os.path.join(datadir, 'injectorG/normalized_000.000.tiff') img180 = os.path.join(datadir, 'injectorG/normalized_180.000.tiff') img0 = io.ImageFile(img0) img180 = io.ImageFile(img180) from imars3d.tilt.use_centers import computeTilt computeTilt(img0, img180, workdir="_tmp.use_centers", sigma=3, maxshift=200) return
def test(): from skimage import feature from imars3d import io dir = os.path.dirname(__file__) datadir = os.path.join(dir, "..", "..", 'iMars3D_data_set') imgpath = os.path.join(datadir, 'injectorG/normalized_000.000.tiff') img = io.ImageFile(imgpath).data edge = feature.canny(img, sigma=3) edge = np.array(edge, dtype="float32") edgeimg = io.ImageFile(path="edge_sigma3.tiff") edgeimg.data = edge edgeimg.save() return
def test(interactive=False): # test data dir = os.path.dirname(__file__) path = os.path.join(dir, "..", "..", "iMars3D_data_set", "20120618_TURBINECT_0180_46_750_0055.fits") img = io.ImageFile(path).getData() assert img.dtype == np.dtype('uint16') # force a pixel to be an outlier img[0, 0] = (1 << 16) - 1 # filter orig_max = np.max(img) img = filters.gamma_filtering.filter_one(img) new_max = np.max(img) assert new_max < orig_max if interactive: # display import pylab pylab.imshow(img) pylab.colorbar() pylab.show()
def test_computeTilt(): img0 = io.ImageFile(os.path.join(datadir, "smoothed_000.000.tiff")).data img180 = io.ImageFile(os.path.join(datadir, "smoothed_180.200.tiff")).data t = direct.computeTilt(img0, img180) assert t > -2 and t < -1 return
def test_shift(): img0 = io.ImageFile(os.path.join(datadir, "cropped_000.000.tiff")).data img180 = io.ImageFile(os.path.join(datadir, "cropped_180.000.tiff")).data flipped_180 = np.fliplr(img180) assert np.isclose(direct.findShift(img0, flipped_180), -78) return
def test_computeTilt(): img0 = io.ImageFile(os.path.join(datadir, "cropped_000.000.tiff")).data img180 = io.ImageFile(os.path.join(datadir, "cropped_180.000.tiff")).data assert np.isclose(direct.computeTilt(img0, img180), 0.4) return
import os import numpy as np import matplotlib.pyplot as plt from imars3d import config, io from imars3d import detector_correction file = './tests/iMars3D_data_set/Low_res_Gdmask_r0000.fits' #print('Does file exist: %s' %os.path.isfile(file)) # retrieve image image_data = io.ImageFile(file).getData() #plt.figure(1) #plt.title("Before") #plt.imshow(image_data, cmap='gray') #plt.colorbar() #plt.show() (detector_width, detector_height) = image_data.shape chip_width = int(detector_width/2) chip_height = int(detector_height/2) # isolate chips data chip1 = image_data[0:chip_height, 0:chip_width] chip2 = image_data[0:chip_height, chip_width:detector_width] chip3 = image_data[chip_height:detector_height, 0:chip_width] chip4 = image_data[chip_height:detector_height, chip_width:detector_width] # init final image
def test_filter_one(): newimg = io.ImageFile('ifced.tiff') newimg.data = ifc.filter_one(img.data, sigma=3) newimg.save() return
#!/usr/bin/env python import os, numpy as np from imars3d.filters import ifc from imars3d import io dir = os.path.dirname(__file__) datadir = os.path.join(dir, "..", "..", "..", 'iMars3D_data_set') imgpath = os.path.join(datadir, 'injectorG/normalized_000.000.tiff') img = io.ImageFile(imgpath) def test_getBoundary(): ifc.getBoundary(img.data, sigma=3, debug=True) return def test_getBG(): print(ifc.getBG(img.data, sigma=3, debug=True)) return def test_filter_one(): newimg = io.ImageFile('ifced.tiff') newimg.data = ifc.filter_one(img.data, sigma=3) newimg.save() return def main():