import numpy as np
from utils import Gcode
-detector = cv2.SimpleBlobDetector_create()
+params = cv2.SimpleBlobDetector_Params()
+
+# Change thresholds
+params.minThreshold = 1
+params.maxThreshold = 256
+
+# Filter by Area.
+params.filterByArea = True
+params.minArea = 50
+
+# # Filter by Convexity
+# params.filterByConvexity = True
+# params.minConvexity = 0.87
+
+# # Filter by Inertia
+# params.filterByInertia = True
+# params.minInertiaRatio = 0.01
+
+
+detector = cv2.SimpleBlobDetector_create(params)
img = cv2.imread('salad.jpg')
+wht = cv2.imread('wht.jpg')
kernelOpen=np.ones((3,3))
kernelClose=np.ones((7,7))
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lowerBound, upperBound)
+mask=cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernelOpen, iterations = 2)
+mask=cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernelClose)
maskImg = cv2.bitwise_and(img,img, mask= mask)
+maskImg = 255 - maskImg
+
points = detector.detect(maskImg)
-print(points)
+
+for i in points:
+ print i.pt
img = cv2.drawKeypoints(img, points, np.array([]), (255,0,0), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
-cv2.imshow('REEE', img)
+cv2.imshow('REEE', maskImg)
+cv2.imshow('wut', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
-
-# mask=cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernelOpen, iterations = 2)
-# mask=cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernelClose)
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