A4 Q4 Done

Author: kvatz

Assignment-4/Data/Q4-output/NewImage2.png

@@ -21,21 +21,29 @@
 print("Image{}.shape: {}".format(3, Image3.shape))
 
 # ----------------------------------------
-
-# Image1 = cv2.resize(Image1)
+new_img = np.zeros((Image2.shape[0], Image1.shape[1]+Image2.shape[1]+Image3.shape[1], 3), dtype=np.uint8)
+new_img[0:Image2.shape[0], Image1.shape[1]:Image1.shape[1]+Image2.shape[1]] = Image2
+NewImage2 = new_img
+cv2.imwrite("./Data/Q4-output/NewImage2.png", NewImage2)
 
 # Panarama Stiching ----------------------
+FinalImageSize = NewImage2.shape
+copySize = Image1.shape[1]
 
 PS = PanoramaStiching()
 
-Result1, Visualization1 = PS.StichImages(Image2, Image1)
+Result1, Visualization1 = PS.StichImages(Image1, NewImage2, FinalImageSize)
+Result1 = PS.Format(Result1, Image2, copySize)
 cv2.imwrite(SAVE + "result1.png", Result1)
 cv2.imwrite(SAVE + "Visualization1.png", Visualization1)
 
-# Result2, Visualization2 = PS.StichImages(Image3, Image2)
+# Result2, Visualization2 = PS.StichImages(Image3, Image2, FinalImageSize)
 # cv2.imwrite(SAVE + "result2.png", Result2)
 # cv2.imwrite(SAVE + "Visualization2.png", Visualization2)
 
-Result3, Visualization3 = PS.StichImages(Image3, Result1)
+copySize = Image1.shape[1] + Image2.shape[1]
+Result3, Visualization3 = PS.StichImages(Image3, Result1, FinalImageSize)
+Result3 = PS.Format2(Result3, Result1, copySize)
 cv2.imwrite(SAVE + "result3.png", Result3)
 cv2.imwrite(SAVE + "Visualization3.png", Visualization3)
+

Assignment-4/Data/Q4-output/Visualization1.png

@@ -11,22 +11,28 @@ class PanoramaStiching:
     def __init__(self):
         return 
 
-    # def combine_images(self, img0, img1, h_matrix):
-    #     points0 = np.array([[0, 0], [0, img0.shape[0]], [img0.shape[1], img0.shape[0]], [img0.shape[1], 0]], dtype=np.float32)
-    #     points0 = points0.reshape((-1, 1, 2))
-    #     points1 = np.array([[0, 0], [0, img1.shape[0]], [img1.shape[1], img0.shape[0]], [img1.shape[1], 0]], dtype=np.float32)
-    #     points1 = points1.reshape((-1, 1, 2))
-    #     points2 = cv2.perspectiveTransform(points1, h_matrix)
-    #     points = np.concatenate((points0, points2), axis=0)
-    #     [x_min, y_min] = np.int32(points.min(axis=0).ravel() - 0.5)
-    #     [x_max, y_max] = np.int32(points.max(axis=0).ravel() + 0.5)
-    #     H_translation = np.array([[1, 0, -x_min], [0, 1, -y_min], [0, 0, 1]])
-
-    #     output_img = cv2.warpPerspective(img1, H_translation.dot(h_matrix), (x_max - x_min, y_max - y_min))
-    #     output_img[-y_min:img0.shape[0] - y_min, -x_min:img0.shape[1] - x_min] = img0
-    #     return output_img
-
-    def StichImages(self, img1, img2):
+    # def RemoveBorder(self, image):
+    #     gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    #     _, thresh = cv2.threshold(gray, 1, 255, cv2.THRESH_BINARY)
+    #     contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    #     cnt = contours[0]
+    #     x,y,w,h = cv2.boundingRect(cnt)
+    #     crop = image[y : y+h, x : x+w]
+    #     return crop
+    
+    def Format(self, res, img, width):
+        print(res.shape)
+        print(width, img.shape[1])
+        res[0:img.shape[0], width : width+img.shape[1]] = img
+        return res
+
+    def Format2(self, res, img, width):
+        print(res.shape)
+        print(width, img.shape[1])
+        res[0:img.shape[0], 0 : width] = img[0:img.shape[0], 0 : width]
+        return res
+
+    def StichImages(self, img1, img2, resultSize):
 
         kp1, des1 = self.DetectKeyPoints(img1)
         kp2, des2 = self.DetectKeyPoints(img2)
@@ -38,23 +44,16 @@ def StichImages(self, img1, img2):
 
         FinalMatches, Homography, Status = Matches
 
-        # Result = self.combine_images(img1, img2, Homography)
-
         # stiching the images based on the Homography
-        Result = cv2.warpPerspective(img1, Homography, (img1.shape[1] + img2.shape[1], max(img1.shape[0], img2.shape[0])))
+        Result = cv2.warpPerspective(img1, Homography, (resultSize[1], resultSize[0]))
+
+        # Result = cv2.warpPerspective(img1, Homography, (img1.shape[1] + img2.shape[1], max(img1.shape[0], img2.shape[0])))
+        cv2.imwrite("./Data/Q4-output/temp.png", Result)
         # cv2.imshow("Result", Result)
         # cv2.waitKey(0)
-        # for i in range(img2.shape[0]):
-        #     for j in range(img2.shape[1]):
-        #         if img2[i, j, 0] == 0 and img2[i, j, 1] == 0 and img2[i, j, 2] == 0:
-        #             continue
-        #         Result[i, j, 0] = img2[i, j, 0]
-        #         Result[i, j, 1] = img2[i, j, 1]
-        #         Result[i, j, 2] = img2[i, j, 2]
-
-        # Result = cv2.resize(Result, None, fx=Result.shape[0], fy=Result.shape[1], interpolation = cv2.INTER_CUBIC)
-        Result[0 : img2.shape[0], 0 : img2.shape[1]] = img2
-
+        # Result[0 : img2.shape[0], 0 : img2.shape[1]] = img2
+        # Result = self.RemoveBorder(Result)
+        
         StichedImage = self.DrawMatches(img1, img2, kp1, kp2, FinalMatches, Status)
         return Result, StichedImage