def _scaleTo8bit(self, img):
'''
The pattern comparator need images to be 8 bit
-> find the range of the signal and scale the image
'''
r = scaleSignalCutParams(img, 0.02) # , nSigma=3)
self.signal_ranges.append(r)
return toUIntArray(img, dtype=np.uint8, range=r)
def export(img, path):
if self.pResize.value():
img = cv2.resize(img, (self.pHeight.value(), self.pWidth.value()) )
else:
img = img.copy()
int_img = toUIntArray(img,
cutNegative=self.pCutNegativeValues.value(),
cutHigh=~self.pStretchValues.value())
cv2.imwrite(path,out(int_img))
print 'Saved image under %s' %path
def imwrite(path, img, dtype=None, cmap=None, **kwargs):
'''
accepted file types are...
for 8 and 16 bit grayscale and RGB images:
Windows bitmaps - *.bmp, *.dib
JPEG files - *.jpeg, *.jpg, *.jpe
JPEG 2000 files - *.jp2
Portable Network Graphics - *.png
WebP - *.webp
Portable image format - *.pbm, *.pgm, *.ppm
Sun rasters - *.sr, *.ras
TIFF files - *.tiff, *.tif
for binary (bool) masks:
*.png
for 32 bit float images:
*.tiff
dtype = (None, float,bool)
all other dtypes are converted to either uint8 or uint16
cmap = display grayscale as rgb using colormap: 'flame', 'gnuplot2' etc.
'''
if dtype in (float, np.float64, np.float32):
assert path.endswith('.tiff') or path.endswith(
'.tif'), 'float arrays can only be saved as TIFF/TIF images'
from PIL import Image
Image.fromarray(np.asfarray(img)).save(path)
# ... PIL is about 3x faster than tifffile.imwrite
elif dtype in (bool, np.bool):
# this method at about 10x slower than cv2.imwrite
# however, it generates 8x smaller images (1bit vs 8bit)
assert path.endswith(
'.png'), 'boolean masks can only be saved as PNG images'
assert img.ndim == 2, 'can only save grayscale images as type(bool)'
from png import Writer
with open(path, 'wb') as f:
s0, s1 = img.shape
w = Writer(s1, s0, greyscale=True, bitdepth=1)
if not img.dtype == np.uint16:
img = img.astype(np.uint8)
w.write(f, img)
else:
img = toUIntArray(img, dtype=dtype, **kwargs)
if cmap is not None:
assert img.ndim == 2, '<cmap> can only be used for grayscale images'
img = applyColorMap(img, cmap)
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
return cv2.imwrite(path, img)
def fn(path, img):
r = self.pRange.value()
if r == '0-max':
r = (0, w.levelMax)
elif r == 'min-max':
r = (w.levelMin, w.levelMax)
else: # 'current'
r = w.ui.histogram.getLevels()
int_img = toUIntArray(img,
# cutNegative=self.pCutNegativeValues.value(),
cutHigh=~self.pStretchValues.value(),
range=r,
dtype={'8 bit': np.uint8,
'16 bit': np.uint16}[self.pDType.value()])
if isColor(int_img):
int_img = cv2.cvtColor(int_img, cv2.COLOR_RGB2BGR)
cv2.imwrite(path, transpose(int_img))
def fn(path, img):
r = self.pRange.value()
if r == '0-max':
r = (0, w.levelMax)
elif r == 'min-max':
r = (w.levelMin, w.levelMax)
else: #'current'
r = w.ui.histogram.getLevels()
int_img = toUIntArray(
img,
# cutNegative=self.pCutNegativeValues.value(),
cutHigh=~self.pStretchValues.value(),
range=r,
dtype={
'8 bit': np.uint8,
'16 bit': np.uint16
}[self.pDType.value()])
cv2.imwrite(path, out(int_img))
def _changeArrayDType(img, dtype, **kwargs):
if dtype == 'noUint':
return toNoUintArray(img)
if issubclass(np.dtype(dtype).type, np.integer):
return toUIntArray(img, dtype, **kwargs)
return img.astype(dtype)
def imwrite(name, arr, **kwargs):
return cv2.imwrite(name, toUIntArray(arr, **kwargs))
def _to8bitImg(img):
if img.dtype == np.uint8:
return img
r = signalRange(img)
return toUIntArray(img, dtype=np.uint8, range=r)
def imwrite(name, arr, dtype=None, **kwargs):
if dtype in (float, np.float64, np.float32):
# save as 32bit float tiff
Image.fromarray(np.asfarray(arr)).save(name)
else:
return cv2.imwrite(name, toUIntArray(arr, dtype=dtype, **kwargs))
# dist = img2.copy()#pc.distort(img2, rotX=10, rotY=20)
dist = pc.distort(img2, rotX=10, rotY=20)
dist2 = dist.copy()
pc.draw3dCoordAxis(dist2, thickness=2)
pc.drawQuad(dist2, thickness=2)
depth = pc.depthMap() # , distance=0)
bg = dist[:, :, 0] < 10
depth[bg] = depth.mean()
print('depth min:%s, max:%s' % (depth.min(), depth.max()))
# 3a. CORRECT WITH QUAD:
corr = pc.correct(dist)
# 3b. CORRECT WITH WITHEN REFERENCE IMAGE
pc.img = dist
pc.setReference(img)
corr2 = pc.correct(dist)
##################
if 'no_window' not in sys.argv:
cv2.imshow("1. original", img2)
cv2.imshow("2. distorted", toUIntArray(dist2, dtype=np.uint8))
cv2.imshow("3a. corr. with quad", toUIntArray(corr, dtype=np.uint8))
cv2.imshow("depth", toUIntArray(depth, cutHigh=False, dtype=np.uint8))
cv2.imshow(
"3b. corr. with ref. image", toUIntArray(corr2, dtype=np.uint8))
cv2.waitKey(0)
obj_corners = [(8, 2), (198, 6), (198, 410), (9, 411)]
#LOAD CLASS:
pc = PerspectiveCorrection(img.shape,
do_correctIntensity=True,
obj_height_mm=sy,
obj_width_mm=sx)
pc.setReference(obj_corners)
img2 = img.copy()
pc.drawQuad(img2, thickness=2)
#2. DISTORT THE IMAGE:
dist = pc.distort(img2, rotX=10, rotY=20)
dist2 = dist.copy()
pc.draw3dCoordAxis(dist2, thickness=2)
pc.drawQuad(dist2, thickness=2)
#3a. CORRECT WITH QUAD:
corr = pc.correct(dist)
#3b. CORRECT WITH WITHEN REFERENCE IMAGE
# pc.img = dist
pc.setReference(img)
corr2 = pc.correct(dist)
if 'no_window' not in sys.argv:
cv2.imshow("1. original", img2)
cv2.imshow("2. distorted", toUIntArray(dist2, dtype=np.uint8))
cv2.imshow("3a. corr. with quad", toUIntArray(corr, dtype=np.uint8))
cv2.imshow("3b. corr. with ref. image",
toUIntArray(corr2, dtype=np.uint8))
cv2.waitKey(0)
def imwrite(name, arr, **kwargs):
return cv2.imwrite(name, toUIntArray(arr, **kwargs))
def _changeArrayDType(img, dtype, **kwargs):
if dtype == 'noUint':
return toNoUintArray(img)
if issubclass(np.dtype(dtype).type, np.integer):
return toUIntArray(img, dtype, **kwargs)
return img.astype(dtype)