def wrapper():
#SET 1
im1 = np.array(Image.open('SET1_L.jpg').convert('RGB'))
im2 = np.array(Image.open('SET1_M.jpg').convert('RGB'))
im3 = np.array(Image.open('SET1_R.jpg').convert('RGB'))
#DEFINING THE INPUT IMAGE MATRIX
img_input = np.zeros((3, ), dtype='object')
img_input[0] = im1
img_input[1] = im2
img_input[2] = im3
#GETTING THE FINAL MOSAIC
final_mosaic = mymosaic(img_input)
#PLOTTING THE FINAL MOSAIC
plt.imshow(final_mosaic)
plt.show()
'''
##############################################################################
#SET 2
im1 = np.array(Image.open('SET2_L.jpg').convert('RGB'))
im2 = np.array(Image.open('SET2_M.jpg').convert('RGB'))
im3 = np.array(Image.open('SET2_R.jpg').convert('RGB'))
#DEFINING THE INPUT IMAGE MATRIX
img_input = np.zeros((3,),dtype='object')
img_input[0] = im1
img_input[1]= im2
img_input[2]= im3
#GETTING THE FINAL MOSAIC
final_mosaic = mymosaic(img_input)
#PLOTTING THE FINAL MOSAIC
plt.imshow(final_mosaic)
plt.show()
##############################################################################
'''
'''
# plt.scatter(x=xR+width, y=yR, c='r', s=5)
# plt.plot([x2R[i]+width,x1MR[i]],[y2R[i],y1MR[i]],'y-',linewidth=2)
# plt.show()
# count += 1
# print()
print("HL:")
print(HL)
print("HR:")
print(HR)
print("ransac complete")
#%% Frame Mosaicing
# Call function
img_mosaic = mymosaic(imgL, imgM, imgR, HL, HR)
# Show Mosaic
cv2.namedWindow('Mosaic', cv2.WINDOW_NORMAL)
cv2.resizeWindow('Mosaic', 1200, 400)
cv2.imshow('Mosaic', img_mosaic.astype(np.uint8))
cv2.waitKey(0)
cv2.destroyAllWindows()
#%% OpenCV Sanity Check
## Compute homographies
#src_pts = np.float32([(x,y) for x,y in zip(x2L,y2L)]).reshape(-1, 1, 2)
#dst_pts = np.float32([(x,y) for x,y in zip(x1ML,y1ML)]).reshape(-1, 1, 2)
#hlCV,mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
#src_pts = np.float32([(x,y) for x,y in zip(x2R,y2R)]).reshape(-1, 1, 2)
from matplotlib import pyplot as plt
import cv2
import numpy as np
import utilities
from mymosaic import *
import sys
# more sets of images available in the images/ folder!
imgL = cv2.imread('images/shoemaker-left.jpg')
imgM = cv2.imread('images/shoemaker-middle.jpg')
imgR = cv2.imread('images/shoemaker-right.jpg')
# find left -> middle homography and right->middle homography
HLM = utilities.get_homography(imgL,imgM,False,"L")
HRM = utilities.get_homography(imgR,imgM,False,"R")
canvas = mymosaic(imgL,imgM,imgR,HLM,HRM)
if cv2.imwrite("output.png",canvas):
print("Output saved to output.png")
from PIL import Image
from helper import *
import sys
from mymosaic import *
iarray = [
Image.open("test_img/S1.jpg"),
Image.open("test_img/S2.jpg"),
Image.open("test_img/S3.jpg"),
Image.open("test_img/S5.jpg"),
Image.open("test_img/S6.jpg")
]
mymosaic(iarray)
# Feature Detection
cimg = corner_detector(grayL)
# Adaptive Non-Maximal Suppression
max_pts =
x,y,rmax = anms(cimg, max_pts)
# Feature Descriptors
descsL = feat_desc(grayL, xL, yL)
descsM = feat_desc(grayM, xM, yM)
descsR = feat_desc(grayR, xR, yR)
# Feature Matching
match = feat_match(descs1, descs2)
# RAndom Sampling Consensus (RANSAC)
H, inlier_ind = ransac_est_homography(x1, y1, x2, y2, thresh)
# Frame Mosaicing
img_mosaic = mymosaic(img_input)
# Show Image Code
#cv2.namedWindow('Left Image', cv2.WINDOW_NORMAL)
#cv2.resizeWindow('Left Image', 600, 600)
#cv2.imshow('Left Image',imgL)
#cv2.waitKey(0)
#cv2.destroyAllWindows()