🎉 Barcode detection and recognition first approach

barcode_api/barcode_engine.py

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+import numpy as np
+import cv2
+from pyzbar import pyzbar
+
+
+def grab_contours(cnts):
+    # if the length the contours tuple returned by cv2.findContours
+    # is '2' then we are using either OpenCV v2.4, v4-beta, or
+    # v4-official
+    if len(cnts) == 2:
+        cnts = cnts[0]
+
+    # if the length of the contours tuple is '3' then we are using
+    # either OpenCV v3, v4-pre, or v4-alpha
+    elif len(cnts) == 3:
+        cnts = cnts[1]
+
+    # otherwise OpenCV has changed their cv2.findContours return
+    # signature yet again and I have no idea WTH is going on
+    else:
+        raise Exception(("Contours tuple must have length 2 or 3, "
+            "otherwise OpenCV changed their cv2.findContours return "
+            "signature yet again. Refer to OpenCV's documentation "
+            "in that case"))
+
+    # return the actual contours array
+    return cnts
+
+def deskew(img):
+
+    gray = cv2.bitwise_not(img)
+
+    # threshold the image, setting all foreground pixels to
+    # 255 and all background pixels to 0
+    thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
+    # grab the (x, y) coordinates of all pixel values that
+    # are greater than zero, then use these coordinates to
+    # compute a rotated bounding box that contains all
+    # coordinates
+
+    coords = np.column_stack(np.where(thresh > 0))
+    angle = cv2.minAreaRect(coords)[-1]
+
+    # the `cv2.minAreaRect` function returns values in the
+    # range [-90, 0); as the rectangle rotates clockwise the
+    # returned angle trends to 0 -- in this special case we
+    # need to add 90 degrees to the angle
+    if angle < -45:
+        angle = -(90 + angle)
+
+    # otherwise, just take the inverse of the angle to make
+    # it positive
+    else:
+        angle = -angle
+
+    # rotate the image to deskew it
+    (h, w) = img.shape[:2]
+    center = (w // 2, h // 2)
+    M = cv2.getRotationMatrix2D(center, angle, 1.0)
+    rotated = cv2.warpAffine(img, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
+
+    return rotated, angle
+
+# load the image and convert it to grayscale
+image = cv2.imread("test.jpg")
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+# compute the Scharr gradient magnitude representation of the images
+# in both the x and y direction using OpenCV 2.4
+ddepth = cv2.CV_32F
+gradX = cv2.Sobel(gray, ddepth=ddepth, dx=1, dy=0, ksize=-1)
+gradY = cv2.Sobel(gray, ddepth=ddepth, dx=0, dy=1, ksize=-1)
+
+# subtract the y-gradient from the x-gradient
+gradient = cv2.subtract(gradX, gradY)
+gradient = cv2.convertScaleAbs(gradient)
+
+# blur and threshold the image
+blurred = cv2.blur(gradient, (9, 9))
+(_, thresh) = cv2.threshold(blurred, 225, 255, cv2.THRESH_BINARY)
+
+# construct a closing kernel and apply it to the thresholded image
+kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (21, 7))
+closed = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
+
+# perform a series of erosions and dilations
+closed = cv2.erode(closed, None, iterations = 4)
+closed = cv2.dilate(closed, None, iterations = 4)
+
+# find the contours in the thresholded image, then sort the contours
+# by their area, keeping only the largest one
+cnts = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL,
+                        cv2.CHAIN_APPROX_SIMPLE)
+cnts = grab_contours(cnts)
+c = sorted(cnts, key=cv2.contourArea, reverse=True)[0]
+
+# compute the rotated bounding box of the largest contour
+rect = cv2.minAreaRect(c)
+box = cv2.boxPoints(rect)
+box = np.int0(box)
+scale = 20
+b1 = box[0]
+b2 = box[1]
+b3 = box[2]
+b4 = box[3]
+x = [b1[1], b2[1], b3[1], b4[1]]
+y = [b1[0], b2[0], b3[0], b4[0]]
+x_min = min(x) - scale
+y_min = min(y) - scale
+x_max = max(x) + scale
+y_max = max(y) + scale
+
+out = gray[x_min:x_max,y_min:y_max]
+deskewed, angle = deskew(out)
+# draw a bounding box arounded the detected barcode and display the
+# image
+thresh = cv2.threshold(deskewed, 0, 255, cv2.THRESH_OTSU)[1]
+
+cv2.imshow("deskew", deskewed)
+cv2.waitKey(0)
+cv2.destroyAllWindows()
+
+# Zbar reader
+barcodes = pyzbar.decode(thresh)
+
+# zxing reader
+"""import zxing
+reader = zxing.BarCodeReader()
+barcodes = reader.decode(thresh)"""
+print(barcodes)