# -*- coding: utf-8 -*- """pixelconversion.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1hfdgkYOw8w6DdJqsZx8txmw8INUGxesl """ # pip install pymupdf -q """### Imports""" import fitz from PIL import Image import numpy as np import cv2 import db """### Open PDF and draw a rectangle on it using Fitz""" def openDrawPDF(path): doc = fitz.open(path) out = fitz.open() # output PDF page = doc[0] print(page.rotation) pix = page.get_pixmap() # render page to an image pl=Image.frombytes('RGB', [pix.width,pix.height],pix.samples) img=np.array(pl) img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR) ratio = pix.width / img.shape[1] imgGry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) imgBW=cv2.threshold(imgGry, 250, 255, cv2.THRESH_BINARY_INV)[1] contours, hierarchy = cv2.findContours(imgBW, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) newcontours = contours[2:] areas = [cv2.contourArea(c) for c in newcontours] max_index2 = np.argmax(areas) contour=newcontours[max_index2] area=cv2.contourArea(contour) if area >500: perimeter = cv2.arcLength(contour, True) approx = cv2.approxPolyDP(contour, 0.01* perimeter, True) shape=[] for point in approx: x1, y1 = point[0] shape.append([(int(x1*ratio)),(int(y1*ratio))]) cv2.circle (img, (x1, y1), 5, 255, 5) rotate=0 if page.rect.height > page.rect.width: rectText=fitz.Rect(300, 200, (page.rect.width-80),( page.rect.width+80) ) rotate=0 else: rectText=fitz.Rect(500, 200, (page.rect.height-80),( page.rect.height+80) ) rotate=90 if page.rotation !=0: rect = fitz.Rect(shape[0][1],shape[0][0],shape[2][1],shape[2][0]) else: rect= fitz.Rect(shape[0][0],shape[0][1],shape[2][0],shape[2][1]) annot = page.add_rect_annot( rect=rect ) # 'rectangle' annot.set_colors( fill=(75/255,0,130/255) ,stroke=(75/255,0,130/255) ) annot.set_opacity(0.9) annot.set_border(border=None, width=0) annot.update() text = """Scale Document""" annot1=page.add_freetext_annot(rectText, text, fontsize=45, fontname='helv', border_color=(1,1,1), text_color=(1,1,1), rotate=rotate, align=1) annot1.update() return doc """### Extract color""" def DetectColor(img,color=0): imgCopy=img.copy() imgCopy=cv2.cvtColor(imgCopy,cv2.COLOR_BGR2HSV) tol=5 #tolerance # color=hexRGB(color) h,s,v = cv2.cvtColor(np.uint8([[[color[2],color[1],color[0]]]]),cv2.COLOR_BGR2HSV)[0][0] lower =np.array( [h- tol, 100, 100 ], dtype='uint8') upper = np.array( [h + tol, 255, 255],dtype='uint8') mask = cv2.inRange(imgCopy, lower , upper) detectedColors = cv2.bitwise_and(imgCopy,imgCopy, mask= mask) # Bitwise-AND mask and original image kernel=np.ones((3,3),np.uint8) mask=cv2.dilate(mask,kernel, iterations=5) mask=cv2.erode(mask,kernel, iterations=4) detectedColors=cv2.dilate(detectedColors,kernel, iterations=5) detectedColors=cv2.erode(detectedColors,kernel, iterations=4) detectedColors=cv2.cvtColor(detectedColors,cv2.COLOR_HSV2BGR) detectedColors=cv2.medianBlur(detectedColors,7) # cv2_imshow(detectedColors) return mask """### For backend - calc area and perim""" def getAreaPerimeter(pdfpath, plan): dbx=db.dropbox_connect() md, res =dbx.files_download(path= pdfpath+plan) data = res.content doc=fitz.open("pdf", data) for page in doc: pix = page.get_pixmap(dpi=200) # render page to an image pl=Image.frombytes('RGB', [pix.width,pix.height],pix.samples) img=np.array(pl) print(img.shape) img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR) mask=DetectColor(img,color=(73,0,130)) #detect colored rect drawn on the pdf contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) for contour in contours: area = cv2.contourArea(contour) perimeter = cv2.arcLength(contour, True) return area,perimeter