cleaned up

clustering_precomputed_dbscan.py

@@ -12,20 +12,16 @@ def get_average_xy(list_input, path):
     wr.writerow(["element", "xmin","ymin","xmax","ymax", "ausrichtung","point_xmi_ymi","point_xma_ymi","point_xmi_yma","point_xma_yma"])
     result_df = pandas.DataFrame(columns=["point_xmi_ymi","point_xma_ymi","point_xmi_yma","point_xma_yma","ausrichtung"])
     for element in list_input:
-        #print(len(element))
         xavg_elem = 0
         yavg_elem = 0
         ymin = 100000000
         ymax = 0
         xmin = 100000000
         xmax = 0
-        #print(element)
         newList = []
         check = False
         if len(element) == 5 and not isinstance(element[0], list):
-            #print("bb")
             newList.append(element)
-            #print(len(newList))
             element = newList
         """if len(element) != 5 and isinstance(element[0], list):
             for el in element:
@@ -65,12 +61,9 @@ def get_average_xy(list_input, path):
         result_df.loc[len(result_df)]=[point_xmi_ymi,point_xma_ymi, point_xmi_yma, point_xma_yma,ausrichtung]
 
     resultFile.close()
-    #print(result_df)
     return result_df
 
 def intersects(rectangle1, rectangle2): #using the separating axis theorem, returns true if they intersect, otherwise false
-    #print(rectangle2[0])
-    #for rect in rectangle1:
 
     rect_1_min = eval(rectangle1[0])
     rect_1_max = eval(rectangle1[3])
@@ -92,28 +85,21 @@ def intersects(rectangle1, rectangle2): #using the separating axis theorem, retu
 def dist(rectangle1, rectangle2):
  #get minimal distance between two rectangles
     distance = 100000000
-    #print(rectangle1)
     for point1 in rectangle1[:4]:
         point1 = eval(point1)
-        #print(point1)
         for point2 in rectangle2[:4]:
-            #print(point2)
             point2 = eval(point2)
-            #dist1 = (float(point2[0]) - float(point1[0])) + ((float(point2[1]) - float(point1[1])))
             dist = sqrt(((float(point2[0]) - float(point1[0])))**2 + ((float(point2[1]) - float(point1[1])))**2)
-            #print(dist)
             if dist < distance:
                 distance = dist
         if rectangle1[4] != rectangle2[4]:
             distance = dist + 100
-        #print(intersects(rectangle1,rectangle2))
         if intersects(rectangle1, rectangle2):
             distance = 0
-            #print(rectangle1)
     return distance
 
 def clustering(dm,eps,path):
-    db = DBSCAN(eps=eps, min_samples=1, metric="precomputed").fit(dm)                                                                                        ##3.93 until now, bei 5 shon mehr erkannt, 7 noch mehr erkannt aber auch schon zu viel; GV12 ist 4.5 gut für LH zu wenig
+    db = DBSCAN(eps=eps, min_samples=1, metric="precomputed").fit(dm)
     labels = db.labels_
     n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)
 
@@ -125,9 +111,6 @@ def clustering(dm,eps,path):
 
 def cluster_and_preprocess(result,eps,path):
     result = get_average_xy(result, path) #input: array of arrays, output: either csv file or array of arrays
-
-    #data = pandas.read_csv("/home/bscheibel/PycharmProjects/engineering_drawings_extraction/temporary/list_to_csv_with_corner_points.csv", sep=";")
-    #data = data[["point_xmi_ymi","point_xma_ymi","point_xmi_yma","point_xma_yma","ausrichtung"]]
     result.to_csv(path+"/temporary/blub.csv", sep=";", index=False, header=None)
     with open(path+"/temporary/blub.csv") as csvfile:
         readCSV = csv.reader(csvfile, delimiter=';')

main.py

@@ -1,4 +1,3 @@
-import organize_drawing_according_to_details_new
 import order_bounding_boxes_in_each_block
 import clustering_precomputed_dbscan
 import read_from_clustered_merged
@@ -11,7 +10,6 @@ import sys
 def write_redis(uuid, result, db_params):
     #db = redis.Redis(unix_socket_path='/tmp/redis.sock',db=7)
     db = redis.Redis("localhost")
-    #db = redis.Redis('localhost')
     db.set(uuid, result)
 
 
@@ -19,6 +17,8 @@ def main(uuid, filepath, db, eps):
     #db = redis.ConnectionPool(connection_class=redis.UnixDomainSocketConnection, path="/tmp/redis.sock")
 
     #db  = redis.Redis(unix_socket_path='/tmp/redis.sock')
+
+
     #path = "/home/centurio/Projects/engineering_drawings_extraction"
     path = "/home/bscheibel/PycharmProjects/engineering_drawings_extraction"
     filename = order_bounding_boxes_in_each_block.pdf_to_html(uuid, filepath, path)
@@ -30,7 +30,6 @@ def main(uuid, filepath, db, eps):
             eps = 7
         else:
             eps = 1
-    #print(eps)
     isos, general_tol = order_bounding_boxes_in_each_block.extract_isos(result)
     print(general_tol)
     res = clustering_precomputed_dbscan.cluster_and_preprocess(result,eps, path)
@@ -38,7 +37,6 @@ def main(uuid, filepath, db, eps):
     tables = order_bounding_boxes_in_each_block.get_tables(clean_arrays)
     pretty = regex_clean_new.print_clean(clean_arrays)
     res, details_dict = organize_drawing_according_to_details_new.main_function(pretty, tables)
-    #print(res)
 
     json_isos = json.dumps(isos)
     json_result = json.dumps(res)
@@ -48,15 +46,13 @@ def main(uuid, filepath, db, eps):
     write_redis(uuid+"isos",json_isos, db)
     write_redis(uuid+"eps", str(number_blocks)+","+str(number_words), db)
     write_redis(uuid+"details",json_details ,db)
-    #print(json_details)
-    #print(redis.Redis('localhost').get(uuid+"dims"))
-    #print(result)
+
 
 if __name__ == "__main__":
     uuid = sys.argv[1]
     filename = sys.argv[2]
     db = sys.argv[3]
     eps = sys.argv[4]
-    #eps
     main(uuid,filename, db, eps)
+
 #main("33333", "/home/centurio/Projects/engineering_drawings_extraction/drawings/5152166_Rev04.pdf", "'/tmp/redis.sock', db=7",3)

order_bounding_boxes_in_each_block.py

@@ -39,23 +39,14 @@ def get_bound_box(file):
         abstand_x = abs(float(element[-1][0])-(float(element[0][2])))
         abstand_y = abs(float(element[-1][3])-float(element[0][1]))
         if later_bigger >= -5:
-            #print(abstand_x-abstand_y)
             new_all_elements.append(element)
         else:
             new_element = sorted(element, key=lambda k: [float(k[0])])
             new_all_elements.append(new_element)
-
-
-    """for element in new_all_elements:
-        for blub in element:
-            #print(blub[4])
-
-        #print("\n")"""
-
     return new_all_elements, number_blocks, number_words
 
 def pdf_to_html(uuid,filepath, path):
-    filename = path +"/temporary/" +str(uuid)+"out.html" #to app/temporary later
+    filename = path +"/temporary/" +str(uuid)+"out.html"
     subprocess.call(['pdftotext', '-bbox-layout',
                      filepath, filename])
     return filename
@@ -87,16 +78,10 @@ def get_tables(result):
     tables = []
     for element in result:
         new = []
-        #print(element)
         if re.search(reg, element):
             new.extend(result[element])
             new.append(element)
             tables.append(new)
     number = len(tables)
-    #print(tables)
     return tables
 
-
-#file="/home/bscheibel/PycharmProjects/engineering_drawings_extraction/drawings/5152166_Rev04.html"
-#get_bound_box(file)
-#pdf_to_html("/home/bscheibel/PycharmProjects/engineering_drawings_extraction/drawings/5129275_Rev01-GV12.pdf")

organize_drawing_according_to_details_new.py

@@ -1,7 +1,4 @@
-import order_bounding_boxes_in_each_block
 import re
-import csv
-import clustering_precomputed_dbscan
 
 def get_details(result): #search for all details in drawing and store it in list details, first need to append all text elements of one line and then check if regular expression is found in this text element
     reg = r"([A-Z])-\1|([A-Z]\W?[A-Z]?\s?\W\s?\d\d?\s?\s?:\s?\d\d?\s?\W)"
@@ -43,23 +40,19 @@ def get_borders(details, tables):
             secondy_max = second[3]
 
             if secondx_max < firstx_min and abs(firsty_min-secondy_min) < 90 and first != second:  ###check for left side, are there any other details at the left side at a certain y-span
-                #print(first,second)
                 if abs(firstx_min - secondx_max)/2 < distance_xmax:
                     distance_xmax = abs(firstx_min - secondx_max)/2
                     x_min = secondx_max + distance_xmax
             if secondx_min > firstx_max and abs(firsty_min-secondy_min) < 190 and first != second: ####check for right side
                 if abs(secondx_min - firstx_max)/2 < distance_xmin:
-                    #print(first, second)
                     distance_xmin = abs(secondx_min - firstx_max)/2
                     x_max = firstx_max + distance_xmin
             if firsty_min > secondy_max and abs(firstx_min-secondx_min) < 80 and first != second: ####check above
                 if abs(firsty_min - secondy_max)/2 < distance_ymin:
-                    #print(first, second)
                     distance_ymin = abs(firsty_min - secondy_max)/2
                     y_min = firsty_min
             if firsty_max < secondy_min and abs(firstx_min-secondx_min) < 80 and first != second: ####check below
                 if abs(firsty_max - secondy_min)/2 < distance_ymax:
-                    #print(first, second)
                     distance_ymax = abs(firsty_max - secondy_min)/2
                     y_max = secondy_min
 
@@ -76,20 +69,16 @@ def get_borders(details, tables):
 
         ##check if it intersects with tables
         for table in tables:
-            #print(table)
             table_xmin = table[0]
             if "Start drawing" in table[4]:
                 table_xmax = 100000000
             else:
                 table_xmax = table[2]
             table_ymin = table[1]
-            #table_ymax = table[3]
             if y_max > table_ymin:
                 if firstx_min > table_xmin and firstx_min < table_xmax:
-                    #print("blub",first,table, table_xmax)
                     y_max = table_ymin
                 elif x_max > table_xmin and x_max < table_xmax:
-                    #print(first,table)
                     y_max = table_ymin
 
         sections.append((first,x_min, y_min,x_max,y_max))
@@ -99,8 +88,6 @@ def get_borders(details, tables):
     return sections
 
 def intersects(detail, rectangle): #using the separating axis theorem
-    #print(detail)
-
 
     rect1_bottom_left_x = float(detail[1][0])
     rect1_top_right_x = float(detail[1][2])
@@ -119,13 +106,10 @@ def intersects(detail, rectangle): #using the separating axis theorem
 def main_function(result, tables):
     reg = r"([A-Z])-\1|([A-Z]\W?[A-Z]?\s?\W\s?\d\d?\s?\s?:\s?\d\d?\s?\W)"
     details, number = get_details(result)
-    #details.extend(tables)
-    #print(tables)
-    #print(details)
+
     details = sorted(details, key=lambda x: x[0]) #sort by distance from 0,0
     sections = get_borders(details, tables)
 
-    #sections.append(tables)
     section = []
     details_dict = {}
 
@@ -136,7 +120,6 @@ def main_function(result, tables):
             coord.append(sec)
         details_dict[coord_name] = coord
         section.append(list((coord_name,coord)))
-    #print(section)
     for table in tables:
         table[3] = 10000000
         coord = []
@@ -145,7 +128,6 @@ def main_function(result, tables):
             coord.append(tab)
         details_dict[name] = coord
         section.append(list((name,coord)))
-    #print(section)
 
     if number == 0 | len(section) == 0:
             section.append(list(("No details",list((000.000,000.000,100000000.000,10000000.000)))))
@@ -154,29 +136,18 @@ def main_function(result, tables):
     dict = {}
 
     for res in result:
-        #print(res)
         for det in section:
-            help_array = []
             help_dict = {}
-            #print(det)
             if re.match(reg, res): ###damit nicht details zu details zugeordnet werden!!!
                 break
             if intersects(det,result[res]):
                 name = det[0]
-                #help_array.append(res)
-                #help_array.extend(result[res])
                 help_dict[res] = result[res]
-                #print(name)
                 if name in dict:
                     dict[name].update(help_dict)
                 else:
                     dict[name] = help_dict
                 break
 
-    """for dic in dict:
-        print(dic)
-        for d in dict[dic]:
-            print(d)"""
-
     return dict, details_dict
 

read_from_clustered_merged.py

@@ -23,8 +23,6 @@ def read(file):
 
             for elem in row3:
 
-                #print("start")
-                #print(len(elem))
                 if len(row3) == 1:
                     element = elem[4]
                     xmin = float(elem[0])
@@ -37,20 +35,14 @@ def read(file):
                     if isinstance(elem[0],list):
                         merged_elements += elem
 
-                        #print(length, len(merged_elements))
-                        if len(merged_elements) < length:   ####woher weiß ich die länge????
-                            #print("bb", len(merged_elements), len(elem))
+                        if len(merged_elements) < length:
                             continue
 
                         if int(ausrichtung) == 1:
-                            #print(elem)
                             merged_elements = sorted(merged_elements, key=lambda k: [float(k[3])], reverse=True)
 
-                        #print(merged_elements)
 
                         for elemt in merged_elements:
-                            #print(merged_elements)
-                            #print(elem)
                             element += elemt[4] + " "
                             if float(elemt[0]) < xmin:
                                 xmin = float(elemt[0])
@@ -73,13 +65,11 @@ def read(file):
                         if float(elem[3]) > ymax:
                             ymax = float(elem[3])
 
-            #print(element)
             result.append(element)
             coords.append(xmin)
             coords.append(ymin)
             coords.append(xmax)
             coords.append(ymax)
             dict[element] = coords
-            #print("\n")
 
     return dict

temporary/blub.csv

@@ -0,0 +1,330 @@
+[187.180925, 815.746851];[213.724746, 815.746851];[187.180925, 833.267817];[213.724746, 833.267817];3
+[217.300913, 816.360079];[244.143154, 816.360079];[217.300913, 835.440719];[244.143154, 835.440719];3
+[248.020901, 815.746851];[326.284694, 815.746851];[248.020901, 833.267817];[326.284694, 833.267817];3
+[1111.191445, 494.016255];[1124.007599, 494.016255];[1111.191445, 521.039792];[1124.007599, 521.039792];1
+[857.632547, 546.096232];[870.4487, 546.096232];[857.632547, 569.279772];[870.4487, 569.279772];1
+[832.072557, 519.30596];[844.888711, 519.30596];[832.072557, 570.839772];[844.888711, 570.839772];1
+[977.620609, 769.211228];[1000.804027, 769.211228];[977.620609, 782.027838];[1000.804027, 782.027838];3
+[591.940763, 812.619667];[677.33106, 812.619667];[591.940763, 831.815352];[677.33106, 831.815352];3
+[967.300113, 797.508989];[1032.901811, 797.508989];[967.300113, 812.147826];[1032.901811, 812.147826];3
+[769.540692, 816.46685];[851.142478, 816.46685];[769.540692, 833.855725];[851.142478, 833.855725];3
+[655.420738, 835.066843];[721.049117, 835.066843];[655.420738, 853.935153];[721.049117, 853.935153];3
+[745.300702, 835.634036];[751.889104, 835.634036];[745.300702, 853.935153];[751.889104, 853.935153];1
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+[1418.610908, 294.223619];[1441.16683, 294.223619];[1418.610908, 310.919876];[1441.16683, 310.919876];3
+[1451.610894, 284.771268];[1474.166716, 284.771268];[1451.610894, 310.319876];[1474.166716, 310.319876];3
+[1532.270923, 352.755985];[1545.087533, 352.755985];[1532.270923, 397.319841];[1545.087533, 397.319841];1
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