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3D_Build.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[ ]:
+
+
+import copy
+import json
+import os
+import shutil
+import cv2
+import time
+import numpy as np
+from matplotlib import pyplot as plt
+from IPython.display import Image
+import import_ipynb
+from rotate_translate import node
+from parent_child_tree import createtree
+from multipleoperation import *
+from subprocess import run
+import open3d as o3d
+import time
+from pyntcloud import PyntCloud
+
+
+# Below Code generates 2 Contours for a given shape. One 'Outer Contour' and other 'Inner Contour' for a 2 shape .
+# 
+
+# In[ ]:
+
+
+print("Please enter the image view file with extension")
+s=input()
+image=cv2.imread(s)
+imgray=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+ret, thresh = cv2.threshold(imgray,127,255,0,cv2.THRESH_BINARY_INV)
+contours, hierarchy = cv2.findContours(thresh,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_NONE)
+hierarchy,contours = zip(*sorted(zip(hierarchy[0],contours),key = lambda x: cv2.contourArea(x[1]),reverse=True))
+print ("no, of contours = " + str(len(contours)-1))
+cv2.drawContours(image, contours, 1, (0, 255, 0), 2)
+cv2.drawContours(image, contours, 2, (0, 0 , 255), 2)
+cv2.imshow('IMAGE', image)
+cv2.imshow('Image Gray', imgray)
+cv2.waitKey(0)
+
+
+# In[ ]:
+
+
+print("Please enter the image view file with extension")
+s=input()
+image=cv2.imread(s)
+imgray=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+ret, thresh = cv2.threshold(imgray,127,255,0,cv2.THRESH_BINARY_INV)
+contours, hierarchy = cv2.findContours(thresh,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_NONE)
+hierarchy,contours = zip(*sorted(zip(hierarchy[0],contours),key = lambda x: cv2.contourArea(x[1]),reverse=True))
+
+
+# Below Function 'detect()' will determine the shape of a given 2D image on the basis of number of edges in the given Shape . 
+
+# Allowed Shapes for a 2d Image are : Triangle , Square , Rectangle , Pentagon , Hexagon , Circle 
+# 
+
+# In[ ]:
+
+
+def detect(c):
+    perimeter = cv2.arcLength(c, True)
+    approx = cv2.approxPolyDP(c, 0.02 * perimeter , True)
+    if len(approx) == 3:
+        shape = "triangle"
+    elif len(approx) == 4:
+        (x, y, w, h) = cv2.boundingRect(approx)
+        ar = w / float(h)
+        if (ar >= 0.999 and ar <= 1.001):
+            shape = "square" 
+        else:
+            shape = "rectangle"
+    elif len(approx) == 5:
+        shape = "pentagon"
+    elif len(approx) == 6:
+        shape = "hexagon"
+    else:
+        shape = "circle"
+    return shape
+
+
+# In[ ]:
+
+
+d=detect(contours[1])
+print(d)
+
+
+# Below 'Dimensioning()' function stores the image temprory amd gives Image imformation like its 'Shape' and 'Ratio'
+
+# In[ ]:
+
+
+def Dimensioning(userId,view,image):
+    os.makedirs('static/temp', exist_ok=True)
+    img = cv2.imread(image,cv2.IMREAD_UNCHANGED)
+    ratio = 0
+    shape = "unidentified"
+    try:
+        w,h,_=img.shape
+        drawSize = int(h/300)
+        imgrey = cv2.cvtColor(img.copy(),cv2.COLOR_BGR2GRAY)
+        ret, thresh = cv2.threshold(imgrey,127,255,cv2.THRESH_BINARY_INV)
+        contours, hierarchy = cv2.findContours(thresh,cv2.RETR_CCOMP,cv2.CHAIN_APPROX_SIMPLE)
+        hierarchy,contours = zip(*sorted(zip(hierarchy[0],contours),key = lambda x: cv2.contourArea(x[1]),reverse=True))
+        for i,c in enumerate(contours):
+            if(hierarchy[i][3] != -1  or (hierarchy[i][3] == -1 and hierarchy[i][2] == -1) ):
+                M = cv2.moments(c)
+                if(M["m00"] !=0):
+                    cX = int(M["m10"] / M["m00"])
+                    cY = int(M["m01"] / M["m00"])
+                    rect = cv2.minAreaRect(c)
+                    box = cv2.boxPoints(rect)
+                    box = np.int0(box)
+                    x,y,w,h = cv2.boundingRect(c)
+                    shape, cylinder_type = detect(c)              
+                    if(shape == "unidentified"):
+                        continue
+                    if(shape=="triangle" or shape=="pentagon" or shape=="hexagon"):
+                        img = cv2.drawContours(img, [box], 0, (0,0, 255), drawSize)
+                    if(shape=="circle"):
+                        img = cv2.rectangle(img,(x,y),(x+w,y+h),(0, 0, 255),drawSize)
+                        cv2.line(img, (x,y), (x+w,y), (0,255, 0), 2)
+                        ratio = 1/w
+                    else:
+                        cv2.line(img, tuple(box[0]), tuple(box[1]), (0,255, 0), 2)
+                        ratio = 1.0/rect[1][1]
+                    break
+        folder = 'static/temp/' + userId
+        os.makedirs(folder, exist_ok=True)
+        try:
+            os.remove(folder + '/' + view + '.jpg')
+        except: pass
+        path_file = (folder + '/' + view + '.jpg')
+        small = cv2.resize(img, (0,0), fx=0.5, fy=0.5) 
+        cv2.imwrite(path_file,small)
+        ratio = str(ratio)
+        data={'image': path_file,'shape': shape,'ratio': ratio}
+        display(Image(filename = path_file))
+        return data
+    except:
+        print(view + "image not found")
+
+
+# In[ ]:
+
+
+def Convert(userId, front_image, side_image, top_image, fratio, sratio, tratio): 
+    start = time.time() 
+    os.makedirs('static/'+userId, exist_ok=True)
+    img_front = cv2.imread(front_image,cv2.IMREAD_UNCHANGED)
+    img_side = cv2.imread(side_image,cv2.IMREAD_UNCHANGED)
+    img_top = cv2.imread(top_image,cv2.IMREAD_UNCHANGED)
+    fratio = float(fratio)
+    sratio = float(sratio)
+    tratio = float(tratio)
+    filePath = "static/temp/"+userId
+    try:
+        shutil.rmtree(filePath)
+    except OSError as e:
+        print ("Error: %s - %s." % (e.filename, e.strerror))
+    primitive = []
+    object_front = valid_contours(img_front,"front",fratio)
+    re_arrange(object_front,"front")
+    object_side = valid_contours(img_side,"side",sratio)
+    re_arrange(object_side,"side")
+    object_top = valid_contours(img_top,"top",tratio)
+    re_arrange(object_top,"top")
+    minApprox = 0.05
+    primitive = combining(object_front,object_side,object_top,minApprox)
+    final = []
+    for set in primitive:
+        for shape in set:
+            final.append(shape[0])
+    try:
+        os.remove('static/' + userId + "/" + userId + '.scad')
+    except: pass
+    path_file = ('static/' + userId + "/" + userId + '.scad')
+    if(len(final) == 0):
+        path_file = 'static/error.txt'
+        f = open(path_file, "w")
+        f.write("Cannot determine the 3d geometry, check your files again!")
+        f.close()
+    createtree(final,path_file)
+    end = time.time() 
+    print("Total time taken to convert:",end-start)
+    return path_file
+
+
+# In[ ]:
+
+
+userId="1"
+front_image = "TestBench/"+userId+"/front.jpg"
+side_image = "TestBench/"+userId+"/side.jpg"
+top_image = "TestBench/"+userId+"/top.jpg"
+front_image
+
+
+# In[ ]:
+
+
+d1 = Dimensioning(userId,"front",front_image)
+d1
+
+
+# In[ ]:
+
+
+d2 = Dimensioning(userId,"side",side_image)
+d2
+
+
+# In[ ]:
+
+
+d3 = Dimensioning(userId,"top",top_image)
+d3
+
+
+# In[ ]:
+
+
+fratio = float(d1["ratio"]) * 2 
+sratio = float(d2["ratio"]) * 2
+tratio = float(d3["ratio"]) * 2
+
+
+# Convert Function joins the multiple 2D images with their respective Ratio to insert them in a tree to form a 3D model from it .
+# If the given shape consist of more than one shape (complex object in Image object) Than we will sub divide it to individual shapes and store them in tree as Parent and Child . 
+
+# In[ ]:
+
+
+Convert(userId,front_image, side_image, top_image,fratio, sratio, tratio)
+
+
+# Point Cloud Representation of the generated Scad File 
+# 
+
+# In[ ]:
+
+
+print("please wait generating 3D view...") 
+start = time.time() 
+scad_filename = "static/" + userId + '/' + userId + ".1.scad"
+stl_filename = "static/" + userId + '/' + userId + ".stl"
+pcd_filename = "static/" + userId + '/' + userId + ".pcd"
+if(os.path.isfile(scad_filename)):
+    run("openscad.exe -o " + stl_filename + " " + scad_filename)
+    if(os.path.isfile(stl_filename)):
+        print("stl file generated at " + stl_filename)
+        mesh = o3d.io.read_triangle_mesh(stl_filename)
+        pointcloud = mesh.sample_points_poisson_disk(100000)
+        o3d.io.write_point_cloud(pcd_filename, pointcloud)
+        model = PyntCloud.from_file(pcd_filename)
+        print("pcd file generated at " + pcd_filename)
+        model.plot() 
+        end = time.time() 
+        print("Total time taken to convert from stl to point cloud:",end-start)
+    else:
+        print("file not found")
+else:
+    print("scad file not found")
+