from util.blending_average import blending_average
from util.draw import Draw
from util.gradient import calclulate_gradient, calculate_gradient_graph, gradient_gradient
from util.image_info import Image_info
import optimization
import texture_mapping
from util.triangle_similar import get_triangle_coefficient
if __name__ == '__main__':
src = cv2.imread("image/DSC00318.JPG")
dst = cv2.imread("image/DSC00319.JPG")
cv2.imshow("src", src)
cv2.imshow("dst", dst)
match = Match(src, dst)
match.getInitialFeaturePairs()
src_point = match.src_match
dst_point = match.dst_match
draw = Draw()
H, no = cv2.findHomography(src_point, dst_point)
img_info = Image_info()
img_info.get_final_size(src, dst, H)
# TODO stitching tow image by global homography, the fusion methed is feathering
src_warp = cv2.warpPerspective(src, H, (img_info.width, img_info.height))
dst_warp = np.zeros_like(src_warp)
dst_warp[img_info.offset_y:dst.shape[0] + img_info.offset_y,
img_info.offset_x:dst.shape[1] +
img_info.offset_x, :] = dst[:, :, :]
from util.blending_average import blending_average
from util.draw import Draw
from util.gradient import calclulate_gradient, calculate_gradient_graph, gradient_gradient
from util.image_info import Image_info
import optimization
import texture_mapping
from util.triangle_similar import get_triangle_coefficient
if __name__ == '__main__':
img1 = cv2.imread("image/DSC00319.JPG")
img2 = cv2.imread("image/DSC00318.JPG")
img3 = cv2.imread("image/DSC00317.JPG")
cv2.imshow("img1", img1)
# 求img1，img2的匹配信息
match_1_2 = Match(img1, img2)
match_1_2.getInitialFeaturePairs()
img1_point = match_1_2.src_match
img2_point = match_1_2.dst_match
H_1_2, no = cv2.findHomography(img2_point, img1_point)
# 求img2,img3的匹配信息
match_2_3 = Match(img2, img3)
match_2_3.getInitialFeaturePairs()
img2_point = match_2_3.src_match
img3_point = match_2_3.dst_match
H_2_3, no = cv2.findHomography(img3_point, img2_point)
H_1_3 = H_1_2.dot(H_2_3)