format code

main.py

@@ -15,6 +15,7 @@ itemh = 0
 def midpoint(ptA, ptB):
     return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)
 
+
 def sizeVexScrew(iteml):
     # Screw Sizing code
     # subtract screw head size to find thread length
@@ -26,6 +27,7 @@ def sizeVexScrew(iteml):
     iteml /= 8
     return iteml
 
+
 def sizeStandoff(iteml):
     # Standoff Sizing code
     iteml *= 2
@@ -40,17 +42,20 @@ def larger(a, b):
     else:
         return b
 
+
 def smaller(a, b):
     if a < b:
         return a
     else:
         return b
 
+
 def near(a, b, close):
     if abs(a-b) < close:
         return True
     return False
 
+
 def swap(a, b):
     tmp = a
     a = b
@@ -76,7 +81,8 @@ if type(args["number"]) == type(selected):
 # load the image, convert it to grayscale, and blur it slightly
 image = cv2.imread(args["image"])
 #image = cv2.resize(image, (int(image.shape[1]*1), int(image.shape[0]*1)))
-image = cv2.resize(image, (1000, int(image.shape[0]/image.shape[1] * 1000)), interpolation = cv2.INTER_NEAREST)
+image = cv2.resize(image, (1000, int(
+    image.shape[0]/image.shape[1] * 1000)), interpolation=cv2.INTER_NEAREST)
 
 if args2.show:
     cv2.namedWindow("Item Sorter")
@@ -107,9 +113,6 @@ pixelsPerMetric = None
 num = 0
 
 
-
-
-
 # Calibration loop
 for c in cnts:
     # if the contour is not sufficiently large, ignore it
@@ -126,8 +129,10 @@ for c in cnts:
     (blbrX, blbrY) = midpoint(bl, br)
     (tlblX, tlblY) = midpoint(tl, bl)
     (trbrX, trbrY) = midpoint(tr, br)
-	dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) - np.array((blbrX, blbrY, 0)))
-	dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) - np.array((trbrX, trbrY, 0)))
+    dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) -
+                        np.array((blbrX, blbrY, 0)))
+    dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) -
+                        np.array((trbrX, trbrY, 0)))
     area_box = dA * dB
     (x, y), radius = cv2.minEnclosingCircle(c)
     area_contour = cv2.contourArea(c)
@@ -155,7 +160,6 @@ for c in cnts:
         pixelsPerMetric = smaller(dA, dB) / args["width"]
 
 
-
 orig = image.copy()
 # loop over the contours individually
 for c in cnts:
@@ -166,7 +170,6 @@ for c in cnts:
         continue
     # compute the rotated bounding box of the contour
 
-
     box = cv2.minAreaRect(c)
     box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
     box = np.array(box, dtype="int")
@@ -200,9 +203,10 @@ for c in cnts:
 
     # draw lines between the midpoints
 # compute the Euclidean distance between the midpoints
-	dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) - np.array((blbrX, blbrY, 0)))
-	dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) - np.array((trbrX, trbrY, 0)))
-
+    dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) -
+                        np.array((blbrX, blbrY, 0)))
+    dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) -
+                        np.array((trbrX, trbrY, 0)))
 
     dimA = dA / pixelsPerMetric
     dimB = dB / pixelsPerMetric
@@ -223,7 +227,6 @@ for c in cnts:
             circular = True
             cv2.circle(orig, (int(x), int(y)), int(radius), (0, 255, 0), 1)
 
-		
         objtype = "Unknown"
         itemw = larger(dimA, dimB)
         itemwr = itemw
@@ -283,7 +286,8 @@ for c in cnts:
             swap(xpos, xpos2)
             swap(ypos, ypos2)
         if rectangular:
-			cv2.line(orig,(int(xpos),int(ypos)),(int(xpos2), int(ypos2)),(0,255,0),1)
+            cv2.line(orig, (int(xpos), int(ypos)),
+                     (int(xpos2), int(ypos2)), (0, 255, 0), 1)
         # print(str(iteml))
         # draw the object sizes on the image
         if args2.show:
@@ -291,7 +295,8 @@ for c in cnts:
             #	(int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
             #	0.65, (255, 255, 255), 2)
             cv2.putText(orig, str(objtype),
-				(int(xpos2 + 10), int(ypos2 + 20)), cv2.FONT_HERSHEY_SIMPLEX,
+                        (int(xpos2 + 10), int(ypos2 + 20)
+                         ), cv2.FONT_HERSHEY_SIMPLEX,
                         0.65, (255, 255, 255), 2)
             output = ""
             if objtype == "Unknown":
@@ -301,7 +306,8 @@ for c in cnts:
             if objtype == "Axle":
                 output = "{:.2f}in".format(iteml)
             cv2.putText(orig, output,  # print data
-				(int(xpos2 + 10), int(ypos2 + 40)), cv2.FONT_HERSHEY_SIMPLEX,
+                        (int(xpos2 + 10), int(ypos2 + 40)
+                         ), cv2.FONT_HERSHEY_SIMPLEX,
                         0.65, (255, 255, 255), 2)
 
     # show the output image