semifunctional capball and particle detection and differentiationstable

1 files changed, 5 insertions, 3 deletions

diff --git a/proc.py b/proc.py
index 7bdef13..607d424 100644
--- a/proc.py
+++ b/proc.py
@@ -17,8 +17,10 @@ h,s,v = cv2.split(himg)
 #blue is 195-135, 40? really that much?
 #hue only testing, not very effective.
 # better with saturation
-thresh = cv2.bitwise_and(cv2.bitwise_or(thresh(h,0,10),thresh(h,169,180)), thresh(s,60,255))
-#thresh = cv2.bitwise_and(thresh(h,95,135), thresh(s,60,255))
+#red
+#thresh = cv2.bitwise_and(cv2.bitwise_or(thresh(h,0,10),thresh(h,169,180)), thresh(s,60,255))
+#blue
+thresh = cv2.bitwise_and(thresh(h,95,135), thresh(s,60,255))
 #thresh = cv2.GaussianBlur(thresh,(29,29),0,0,cv2.BORDER_REFLECT_101)
 cv2.imwrite("stallmask.jpg",thresh);
 mask = cv2.merge((thresh,thresh,thresh))
@@ -28,7 +30,7 @@ cv2.imwrite("stallmasked.jpg",cv2.cvtColor(masked,cv2.COLOR_HSV2BGR));
 im2, con, heir = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
 v = 0
 for i in range(0, len(con)) :
-	if (cv2.contourArea(con[i]) > 2000) :
+	if (cv2.contourArea(con[i]) > 1000) :
 		a = cv2.contourArea(con[i])
 		cv2.drawContours(masked, con, i, (120,255,255), 5)
 		(cx, cy), r = cv2.minEnclosingCircle(con[i])