update

.gitignore

@@ -3,8 +3,7 @@
 storeDigitData/
 .DS_Store
 test.py
-algorithm/OCR/newNet/images/
-testImages
+IMAGES
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

algorithm/Blenometer.py → Algorithm/Blenometer.py

@@ -1,9 +1,7 @@
 import functools
-from algorithm.debug import *
-import numpy as np
 
-from algorithm.Common import *
-from algorithm.debug import *
+from Algorithm.utils.Finder import *
+from configuration import *
 
 
 def cmp(contour1, contour2):
@@ -71,7 +69,6 @@ def checkBleno(image, info):
     return res
 
 
-
 def readBlenometerStatus(image, info):
     print("Blenometer Reader called!!!")
     if image is None:

algorithm/OCR/newNet/train.py → Algorithm/OCR/newNet/train.py

@@ -1,5 +1,5 @@
-from algorithm.OCR.newNet.dataLoader import *
-from algorithm.OCR.newNet.LeNet import *
+from Algorithm.OCR.newNet.dataLoader import *
+from Algorithm.OCR.newNet.LeNet import *
 
 import sys
 sys.path.append("../LeNet")

algorithm/OCR/test_ocr.py → Algorithm/OCR/test_ocr.py

@@ -1,5 +1,5 @@
 import cv2
-from algorithm.OCR.utils import *
+from Algorithm.OCR.utils import *
 
 net = newNet()
 

algorithm/OCR/utils.py → Algorithm/OCR/utils.py

@@ -1,10 +1,10 @@
 import sys
+
 import cv2
-import os
 import numpy as np
 import torch
 
-from algorithm.debug import *
+from configuration import *
 
 sys.path.append(".")
 
@@ -31,11 +31,11 @@ def __init__(self):
         :return:
         """
         sys.path.append("newNet")
-        from algorithm.OCR.newNet.LeNet import myNet
+        from Algorithm.OCR.newNet.LeNet import myNet
 
         self.net = myNet()
         self.net.eval()
-        self.net.load_state_dict(torch.load("algorithm/OCR/newNet/net.pkl"))
+        self.net.load_state_dict(torch.load("Algorithm/OCR/newNet/net.pkl"))
 
     def recognizeNet(self, image):
         """
@@ -52,7 +52,7 @@ def recognizeNet(self, image):
         num = int(np.array(predicted[0]).astype(np.uint32))
 
         if ifShow:
-            print(num)
+            print("this number is: ", num)
             cv2.imshow("single", image)
             cv2.waitKey(0)
 

algorithm/SF6.py → Algorithm/SF6.py

@@ -1,5 +1,6 @@
-from algorithm.Common import *
-from algorithm.debug import *
+from Algorithm.utils.Finder import *
+from Algorithm.utils.AngleFactory import AngleFactory
+from configuration import *
 
 
 def SF6Reader(image, info):

algorithm/absorb.py → Algorithm/absorb.py

@@ -1,7 +1,7 @@
 import json
-import numpy as np
+
 import cv2
-from algorithm.Common import AngleFactory, meterFinderByTemplate
+import numpy as np
 
 
 # type transform

algorithm/arrest/countArrester.py → Algorithm/arrest/countArrester.py

@@ -3,11 +3,7 @@
 @author: maoyingxue
 """
 
-import json
-
-from algorithm.debug import *
-from algorithm.Common import *
-from algorithm.pressure.normalPressure import normalPressure
+from Algorithm.utils.Finder import *
 
 
 def countArrester(image, info):
@@ -63,7 +59,7 @@ def countArrester(image, info):
         cv2.imshow("test", image)
         cv2.waitKey(0)
 
-    #value = calAngleBetweenTwoVector(np.array(startPoint)-centerPoint,pointerPoint-centerPoint)
+    # value = calAngleBetweenTwoVector(np.array(startPoint)-centerPoint,pointerPoint-centerPoint)
     if len(pointerPoint) == 0:
         return "pointer not found!"
     value = calAngleClockwise(np.array(startPoint), pointerPoint, centerPoint)

algorithm/arrest/doubleArrester.py → Algorithm/arrest/doubleArrester.py

@@ -1,8 +1,13 @@
-import numpy as np
+"""
+@author: Xuyuanyuan
+"""
+
 import cv2
+import numpy as np
 
-from algorithm.debug import *
-from algorithm.Common import scanPointer, meterFinderByTemplate
+from Algorithm.utils.Finder import meterFinderByTemplate
+from Algorithm.utils.ScanPointer import scanPointer
+from configuration import *
 
 
 def doubleArrester(image, info):

algorithm/oilTempreture.py → Algorithm/oilTempreture.py

@@ -1,5 +1,9 @@
-from algorithm.Common import *
-from algorithm.debug import *
+import cv2
+import numpy as np
+
+from Algorithm.utils.Finder import meterFinderBySIFT
+from Algorithm.utils.AngleFactory import AngleFactory
+from configuration import *
 
 red_range = [np.array([156, 120, 80]), np.array([179, 240, 220])]
 white_range = [np.array([0, 0, 200]), np.array([180, 30, 255])]

algorithm/onoff/onoffBatteryScreen.py → Algorithm/onoff/onoffBatteryScreen.py

@@ -1,9 +1,9 @@
-from algorithm.Common import meterFinderBySIFT
-from algorithm.debug import *
-
 import cv2
 import numpy as np
 
+from Algorithm.utils.Finder import meterFinderBySIFT
+from configuration import *
+
 
 def onoffBatteryHardCode(image, info):
     """

algorithm/onoff/onoffIndoor.py → Algorithm/onoff/onoffIndoor.py

@@ -1,10 +1,9 @@
-import math
-import numpy as np
-import cv2
-from algorithm.debug import *
-from algorithm.Common import AngleFactory, meterFinderByTemplate
-from algorithm.Common import *
 import json
+import cv2
+import numpy as np
+
+from Algorithm.utils.Finder import meterLocationFinderBySIFT
+
 
 def HSV(img):
     """
@@ -19,6 +18,7 @@ def HSV(img):
 
     return H, S, V, h, s, v
 
+
 def getBinary(img):
     """
     对图像进行轮廓检测，获取图像的二值图
@@ -27,6 +27,7 @@ def getBinary(img):
     edges = cv2.Canny(gray, 100, 200, apertureSize=3)
     return edges
 
+
 def searchUpBlack(raw, img, x, y):
     """
     :param raw: 原图
@@ -57,6 +58,7 @@ def searchUpBlack(raw, img, x, y):
     # cv2.imwrite("ww.jpg",raw)
     return y, a, y, b
 
+
 def searchRightRed(raw, img, x, y):
     """
     :param raw: 原图
@@ -87,19 +89,20 @@ def searchRightRed(raw, img, x, y):
 
     return y, a, y, b
 
+
 # 裁剪目标区域值
 def cutTarget(img, x1, y1, x2, y2, status):
-
-    if status=="left":
+    if status == "left":
         len = y1 - y2
         start_x = x1 - len
         start_y = y1 - len
-    elif status=="right":
+    elif status == "right":
         len = y1 - y2
-        len = len+15
+        len = len + 15
         start_x = x1
         start_y = y1 - len
-    return img[start_y:start_y + len, start_x:start_x + int(1.4*len)]
+    return img[start_y:start_y + len, start_x:start_x + int(1.4 * len)]
+
 
 # 在H空间里统计某一种颜色出现的比率
 def countTarPer(h_vec, which):
@@ -115,19 +118,20 @@ def countTarPer(h_vec, which):
 
     return n, float(n / N)
 
-#type transform
-def getMatInt(Mat):
 
+# type transform
+def getMatInt(Mat):
     d = Mat.shape
     for i in range(d[2]):
         for n in range(d[0]):
             for m in range(d[1]):
-                Mat[n,m,i] = int(Mat[n,m,i])
+                Mat[n, m, i] = int(Mat[n, m, i])
                 # print(Mat[n,m,i])
     Mat = Mat.astype(np.uint8)
     return Mat
 
-def gamma(image,thre):
+
+def gamma(image, thre):
     """
     :param image: numpy type
     :param thre: float
@@ -140,42 +144,43 @@ def gamma(image,thre):
     out = getMatInt(out * 255)
     return out
 
-def calDis(img,t):
+
+def calDis(img, t):
     t = int(t)
     # print(t)
-    s1=0
-    s2=0
-    h,w = img.shape
-
-    for i in  range(w):
-        if img[t][i]==255:
-            if s1==0:
-                s1=i
-            elif s2==0:
-                s2=i
-    return abs(s2-s1)
+    s1 = 0
+    s2 = 0
+    h, w = img.shape
+
+    for i in range(w):
+        if img[t][i] == 255:
+            if s1 == 0:
+                s1 = i
+            elif s2 == 0:
+                s2 = i
+    return abs(s2 - s1)
+
 
 def judgeStatus(img):
-    h,w = img.shape
-    mid = h/2
+    h, w = img.shape
+    mid = h / 2
 
-    #画三条线
+    # 画三条线
     t1 = mid
-    t2 = mid+3
-    t3=t2+6
-    #计算距离
-    n=0
+    t2 = mid + 3
+    t3 = t2 + 6
+    # 计算距离
+    n = 0
     ts = [t1, t2, t3]
 
     for t in ts:
-        if calDis(img,t)<4:
-         n=n+1
+        if calDis(img, t) < 4:
+            n = n + 1
 
     # print(n)
     return n
 
 
-
 def onoffIndoor(image, info):
     """
     :param image:whole image
@@ -184,12 +189,12 @@ def onoffIndoor(image, info):
     """
     binary = getBinary(image)
     X, Y, _, _ = meterLocationFinderBySIFT(image, info['template'])
-    if info['name']=="onoffIndoor1_1":
+    if info['name'] == "onoffIndoor1_1":
         x1, y1, x2, y2 = searchUpBlack(image, binary, Y, X)
-        img = cutTarget(image, x1, y1, x2, y2,"left")
+        img = cutTarget(image, x1, y1, x2, y2, "left")
         H, _, _, h, _, _ = HSV(img)
-        n,per = countTarPer(h, "black")
-        status="p"
+        n, per = countTarPer(h, "black")
+        status = "p"
         if per > 0.5:
             status = "close"
         res = {
@@ -198,10 +203,10 @@ def onoffIndoor(image, info):
             'per': per
         }
 
-    elif info['name']=="onoffIndoor3_1":
+    elif info['name'] == "onoffIndoor3_1":
         x1, y1, x2, y2 = searchRightRed(image, binary, Y, X)
         img = cutTarget(image, x1, y1, x2, y2, "right")
-        #获取目标区域
+        # 获取目标区域
         img = gamma(img, 0.2)
         # cv2.imwrite("res.jpg", img)
         img = getBinary(img)
@@ -213,7 +218,6 @@ def onoffIndoor(image, info):
             'status': status
         }
 
-
     res = json.dumps(res)
 
     return res