def imread(file):
x = int(file[0])
y = int(file[1])
im = cv2.imread(dir + file, cv2.IMREAD_COLOR)
h, w = im.shape[:2]
rect = Rectangle(Vector(0, 0), 0, 1., h / w)
return Image(rect, im)
def __init__(self, context, images):
self.context = context
self.tiles = np.empty(images.shape, object)
for c in np.ndindex(self.tiles.shape):
images[c].data = context.pre(images[c].data)
from lib.canvas import Image
Image(None, context.features(images[c].data)).show()
self.tiles[c] = TileStitcher.Tile(images[c])
for c in np.ndindex(self.tiles.shape):
self.tiles[c].meet_neighbours(c, self.tiles)
def capture(self, x, y):
"""capture an image and apply our calibration parameters to (un)distort it"""
im = self.backend.get(x, y, *self.shape)
if self.calibration is not None:
_, mat, coe, *_ = self.calibration
im = cv2.undistort(im, mat, coe)
return Image(
Rectangle(Vector(0, 0),
Vector(1, 0).rotate(self.orientation()), *self.shape),
im)
#!/usr/bin/env python3
from lib.stitch import TileStitcher, StitchContext
from lib.canvas import Image, Rectangle, Vector
import numpy as np
import cv2
import os
dir = "./var/stitch/tile2/"
imshow = lambda im: Image(None, im).show()
def imread(file):
x = int(file[0])
y = int(file[1])
im = cv2.imread(dir + file, cv2.IMREAD_COLOR)
h, w = im.shape[:2]
rect = Rectangle(Vector(0, 0), 0, 1., h / w)
return Image(rect, im)
ims = np.empty((2, 1), object)
ims[0, 0] = imread("10.jpg")
ims[1, 0] = imread("20.jpg")
print(ims)
ctx = StitchContext()
ctx.features.hsv(1)
stitcher = TileStitcher(ctx, ims)
im = stitcher.assemble()
#im = stitch_hsv(ims, 1)
#!/usr/bin/env python3
from lib.stitch import TileStitcher, StitchContext
from lib.canvas import Image, Rectangle, Vector
import numpy as np
import cv2
import os
imshow = lambda im: Image(None, im).show()
dir = "./var/stitch/tile%s/" % input("Which? ")
files = os.listdir(dir)
w = max(int(file[0]) for file in files) + 1
h = max(int(file[1]) for file in files) + 1
print(h, w)
ims = np.empty((w, h), object)
for file in files:
x = int(file[0])
y = int(file[1])
im = cv2.imread(dir + file, cv2.IMREAD_COLOR)
h, w = im.shape[:2]
rect = Rectangle(Vector(0, 0), 0, 1., h / w)
ims[x, y] = Image(rect, im)
print(ims)
ctx = StitchContext()
ctx.features.histeq_clr()
stitcher = TileStitcher(ctx, ims)
im = stitcher.assemble()
h, w = im.shape[:2]
im2 = cv2.resize(im, (800, int(800 * h / w)))
def get(self, x, y, w, h):
"""Return a section of the layer;
xy are real-world coordinates
wh are in pixels and correspond to the 'camera' resolution"""
x, y = map(lambda v: int(v*self.factor0), (x, y))
return Image.pil2cv(self.im.read_region((x, y), self.z, (w, h)))
def get(self, x, y, w, h):
"""Return a section of the layer;
xy are real-world coordinates
wh are in pixels and correspond to the 'camera' resolution"""
x, y = map(lambda v: int(v * self.factor0), (x, y))
return Image.pil2cv(self.im.read_region((x, y), self.z, (w, h)))
def capture(self):
im = self.backend.get(0, 0, *self.backend.shape)
return Image(self.calibration, im)