First commit

README.md

@@ -1,2 +1,15 @@
-# carpetHomograpfy
+# Adding carpets to images with homography
 
+### Table of content
+
+1. [Input data](#input-data)
+2. [Getting started](#getting-started)
+
+
+## 1. Input data
+
+As input data a carpet image and a room image are required:
+
+
+
+## 2. Getting started

app.py

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+# Importing the dependencies
+import cv2
+import numpy as np
+
+# Defining variables to store coordinates where the second image has to be placed
+positions = []
+positions2 = []
+count = 0
+
+# Mouse callback function
+def draw_circle(event, x, y, flags, param):
+    global positions, count
+    # If event is Left Button Click then store the coordinate in the lists, positions and positions2
+    if event == cv2.EVENT_LBUTTONUP:
+        cv2.circle(room_draw, (x, y), 2, (255, 0, 0), -1)
+        positions.append([x, y])
+        if count != 3:
+            positions2.append([x, y])
+        elif count == 3:
+            positions2.insert(2, [x, y])
+        count += 1
+
+
+# Reading the two images and storing it in variables room and dp
+room = cv2.imread("./data/room2.jpg")
+room_draw = room.copy()
+
+dp = cv2.imread("./data/carpet.jpeg")
+
+# Defing a window named 'image' and set the callback to define the destination points
+cv2.namedWindow("image")
+cv2.setMouseCallback("image", draw_circle)
+
+while True:
+    cv2.imshow("image", room_draw)
+    k = cv2.waitKey(20) & 0xFF
+    if k == 27 or count > 3:
+        break
+
+cv2.destroyAllWindows()
+
+height, width = room.shape[:2]
+h1, w1 = dp.shape[:2]
+
+pts1 = np.float32([[0, 0], [w1, 0], [0, h1], [w1, h1]])
+pts2 = np.float32(positions)
+
+# Calculate homography
+h, mask = cv2.findHomography(pts1, pts2, cv2.RANSAC, 5.0)
+
+height, width, channels = room.shape
+im1Reg = cv2.warpPerspective(dp, h, (width, height))
+
+# Masking and blending
+mask2 = np.zeros(room.shape, dtype=np.uint8)
+
+roi_corners2 = np.int32(positions2)
+
+channel_count2 = room.shape[2]
+ignore_mask_color2 = (255,) * channel_count2
+
+cv2.fillConvexPoly(mask2, roi_corners2, ignore_mask_color2)
+
+mask2 = cv2.bitwise_not(mask2)
+masked_image2 = cv2.bitwise_and(room, mask2)
+
+# Using Bitwise or to merge the two images
+final = cv2.bitwise_or(im1Reg, masked_image2)
+
+# Show results and write to file
+cv2.imshow("Final", final)
+cv2.imwrite("Final2.jpg", final)
+
+cv2.waitKey(0) & 0xFF
+cv2.destroyAllWindows()

requirements.txt

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+opencv-contrib-python
+numpy
+fire