Initial

sharpening.py

@@ -0,0 +1,67 @@
+import cv2
+import numpy as np
+
+
+
+image  = cv2.imread("digging.jpg")
+
+cv2.imshow("Image", image)
+
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+cv2.imshow("gray", gray)
+
+blur = cv2.GaussianBlur(gray, (5,5), 0)
+cv2.imshow("blur", blur)
+
+thresh = cv2.adaptiveThreshold(blur, 255, 1, 1, 11, 2)
+
+#thresh = cv2.bitwise_not(thresh)
+
+cv2.imshow("thresh", thresh)
+#cv2.waitKey()
+contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+max_area = 0
+c = 0
+for i in contours:
+        area = cv2.contourArea(i)
+        if area > 1000:
+                if area > max_area:
+                    max_area = area
+                    best_cnt = i
+                    image = cv2.drawContours(image, contours, c, (0, 255, 0), 1)
+        c+=1
+
+mask = np.zeros((gray.shape),np.uint8)
+cv2.drawContours(mask,[best_cnt],0,255,-1)
+cv2.drawContours(mask,[best_cnt],0,0,1)
+cv2.imshow("mask", mask)
+
+out = np.zeros_like(gray)
+out[mask == 255] = gray[mask == 255]
+cv2.imshow("New image", out)
+
+blur = cv2.GaussianBlur(out, (5,5), 0)
+cv2.imshow("blur1", blur)
+
+thresh = cv2.adaptiveThreshold(blur, 255, 1, 1, 11, 2)
+thresh = cv2.bitwise_not(thresh)
+cv2.imshow("thresh1", thresh)
+
+contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+squares = []
+c = 0
+for i in contours:
+        area = cv2.contourArea(i)
+        cnt_len = cv2.arcLength(i, True)
+        cnt = cv2.approxPolyDP(i, 0.01 * cnt_len, True)
+        if area > 1000/2:
+            squares.append(cnt)
+            #cv2.drawContours(image, contours, c, (0, 255, 0), 1)
+        c+=1
+cv2.drawContours(image, squares, -1, (0, 255, 0), 1)
+
+cv2.imshow("Final Image", image)
+cv2.waitKey(0)
+cv2.destroyAllWindows()