import sys import platform import glob import cv2 import os import jsonpickle import numpy as np import mysql.connector from flask import Flask, request from PIL import Image from mysql.connector import Error from flask_apscheduler import APScheduler import base64 from io import BytesIO ###### import matplotlib.pyplot as plt import math from scipy import ndimage ##### #print(cv2.__version__) print(sys.version) app = Flask(__name__) threshold = 40 kernel = np.ones((5, 5), np.uint8) global status status="NOT" global isGoodFeatures isGoodFeatures="GOOD" orb = cv2.ORB_create(nfeatures=2000) descriptor = cv2.xfeatures2d.BEBLID_create(0.75) global images images = [] global matchlist matchlist = [] global ClassNames ClassNames = [] global filelist filelist= [] global name APP_ROOT = os.path.dirname(os.path.abspath(__file__)) # refers to application_top APP_STATIC = os.path.join(APP_ROOT, 'arhimaya/Headerimage') APP_STATIC_SAVEDIRECTORY = os.path.join(APP_ROOT, 'arhimaya/ProcessImages') #print(APP_STATIC) for root, dirs, files in os.walk(APP_STATIC): for file in files: # append the file name to the list filelist.append(os.path.join(root, file)) #print(filelist) for name in filelist: newPath = name.replace(os.sep, '/') # print(newPath) # print(name) #print(newPath) imgCur = cv2.imread(newPath, 0) images.append(imgCur) # print(imgCur) ClassNames.append(os.path.splitext(newPath)[0] + os.path.splitext(newPath)[1]) #print(ClassNames) @app.route('/VisionMaya') def VisionMaya(): return 'Welcome to VisionMaya 2.2 UPDATED AUTOSAVE BBLIED' @app.route('/blogs') def blogs(): return 'Welcome1 to The Blog App_Updated' @app.route('/blog/') def blog(id): return "The Blog id is {}".format(id) @app.route('/selva') def selva(): global ClassNames classNames=["sankari","siva"] return jsonpickle.encode(ClassNames) @app.route('/siva') def siva(): global filelist global name global images global ClassNames global matchlist filelist.clear() ClassNames.clear() filelist.clear() images.clear() matchlist.clear() #filelist = [] #print(files) APP_ROOT = os.path.dirname(os.path.abspath(__file__)) # refers to application_top APP_STATIC = os.path.join(APP_ROOT, 'arhimaya/Headerimage') #for files in os.walk('APP_STATIC'): #for filename in files: #fname = os.path.join(dirpath, filename) #if fname.endswith('.jpg'): #print(fname) for root, dirs, files in os.walk(APP_STATIC): for file in files: # append the file name to the list filelist.append(os.path.join(root, file)) #print(filelist) for name in filelist: newPath = name.replace(os.sep, '/') # print(newPath) # print(name) #print(newPath) imgCur = cv2.imread(newPath, 0) images.append(imgCur) # print(imgCur) ClassNames.append(os.path.splitext(newPath)[0] + os.path.splitext(newPath)[1]) #siva="SANKARI" #for dirpath, dirs, files in os.walk('env'): #for filename in files: #fname = os.path.join(dirpath,filename) #siva=siva+'.'+fname #if fname.endswith('.py'): #print(fname) #siva=siva+"New"+fname return jsonpickle.encode(ClassNames) #print(ClassNames) def findDes(images): desList = [] for img in images: #kp, des = orb.detectAndCompute(img, None) kp = orb.detect(img, None) kp, des = descriptor.compute(img, kp) desList.append(des) return desList def findID(img, deslist): kp2 = orb.detect(img, None) kp2, des2 = descriptor.compute(img, kp2) #kp2, des2 = orb.detectAndCompute(img, None) #bf = cv2.BFMatcher() bf = cv2.DescriptorMatcher_create(cv2.DescriptorMatcher_BRUTEFORCE_HAMMING) matchlist.clear() finalvalue = -1 try: for des in deslist: matches = bf.knnMatch(des, des2, k=2) good = [] matched1 = [] matched2 = [] nn_match_ratio = 0.8 # Nearest neighbor matching ratio for m, n in matches: if m.distance < nn_match_ratio * n.distance: #if n < len(matches) - 1 and n.distance < 0.7 * matches[n+1].distance: good.append(des[m.queryIdx]) #matched1.append(kpts1[m.queryIdx]) #matched2.append(kpts2[m.trainIdx]) #print(len(matched1)) matchlist.append(len(good)) except: pass if len(matchlist) != 0: if max(matchlist) > threshold: finalvalue = matchlist.index(max(matchlist)) return finalvalue @app.route('/') def hello_world(): return cv2.__version__ def variance_of_laplacian(image): # compute the Laplacian of the image and then return the focus # measure, which is simply the variance of the Laplacian return cv2.Laplacian(image, cv2.CV_64F).var() @app.route('/post_json', methods=['POST']) def image_check(): # ----- SECTION 1 ----- # File naming process for nameless base64 data. # We are using the timestamp as a file_name. from datetime import datetime dateTimeObj = datetime.now() file_name_for_base64_data = dateTimeObj.strftime("%d-%b-%Y--(%H-%M-%S)") content_type = request.headers.get('Content-Type') if (content_type == 'application/json'): json = request.json #return json['firstName'] else: return 'Content-Type not supported!' # ----- SECTION 2 ----- try: #status=json['lastname'] decoded_img = base64.b64decode(json['firstName']) img = Image.open(BytesIO(decoded_img)) np_data = np.frombuffer(decoded_img,np.uint8) img21 = cv2.imdecode(np_data,cv2.IMREAD_UNCHANGED) #file_name = APP_STATIC_SAVEDIRECTORY+"/"+file_name_for_base64_data + ".jpg" #print(file_name) #img.save(file_name, "jpeg") #print(file_name+"sss") ###############NEW START image=img21 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) fm = variance_of_laplacian(gray) text = "Not Blurry" # if the focus measure is less than the supplied threshold, # then the image should be considered "blurry" if fm < 5.0: text = "Blurry" print(text) isGoodFeatures="FALSE" else: orb1 = cv2.ORB_create() # find the keypoints with ORB kp = orb1.detect(image,None) # compute the descriptors with ORB kp, des = orb.compute(image, kp) # draw only keypoints location,not size and orientation #img2 = cv.drawKeypoints(foreground, kp, None, color=(0,255,0), flags=0) if len(kp)>400: print(len(kp)) img2=image isGoodFeatures="GOOD" #cv2.imwrite('foreground.jpg', img2) else: isGoodFeatures="FALSE" ###############NEW END if isGoodFeatures!="FALSE": desList = findDes(images) #print(len(desList)) #img2 = cv2.imread("test/Suresh.jpg") # Reading the image. Change the name according to your img name imgOriginal = img2.copy() img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY) img_blur = cv2.GaussianBlur(img2, (7, 7), 1) # Making the image blurry img_edges = cv2.Canny(img_blur, 30, 30) # Finding the edges in the image for detecting where the image is. img_dialation = cv2.dilate(img_edges, kernel, iterations=1) # Dilating our image so that the edges detected by canny edge detector can be made thick. contours, hierarchy = cv2.findContours(img2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) # Detecting the contours(shapes) for cnt in contours: area = cv2.contourArea(cnt) # checking the area of contours if area > 5000: # there can be many countours so we are filtering it as our money area is large peri = cv2.arcLength(cnt, True) # Calculating our countour perimeter approx = cv2.approxPolyDP(cnt, 0.02 * peri, True) # performimg an approximation of a shape of a contour. x, y, w, h = cv2.boundingRect(approx) # finding the x, y coordinates and height and width of our money final_img = imgOriginal[y: y + h, x: x + w] # Croping our image to get money only else: final_img = img2 # returning our img2 image if the money is not detected and this situation comes when your image contains only money i.e. their is no any background. X = findID(final_img, desList) print(matchlist) #print(len(matched1)) #print(ClassNames) if X != -1: #status = "Image has been succesfully sent to the server."+ClassNames[X] addurlParent=ClassNames[X] print(addurlParent) #status=ClassNames[X]+jsonpickle.encode(matchlist) connection = mysql.connector.connect(host='localhost', database='arhimaya', user='root', password='Vision@3') sql_select_Query = "select * from others" # MySQLCursorDict creates a cursor that returns rows as dictionaries cursor = connection.cursor(dictionary=True) cursor.execute(sql_select_Query) records = cursor.fetchall() #print("Fetching each row using column name") for row in records: id = row["targetimagepath"] #print(id) #print(addurlParent) #name = row["Name"] #price = row["Price"] if addurlParent == id: targetContent= row["targetcontent"] status = targetContent #print(status+"Finished") break #print(addurlParent+"DONE") #purchase_date = row["Purchase_date"] if connection.is_connected(): connection.close() cursor.close() #print("MySQL connection is closed") #cv2.putText(imgOriginal, ClassNames[X], (50, 50), cv2.FONT_HERSHEY_COMPLEX, 2, (0, 0, 255), 3) #print(status) else: status="WRONG" else: status="WRONG" # ----- SECTION 3 ----- except Exception as e: status = "Error! = " + str(e) return status if __name__ == '__main__': #app.run(host="192.168.1.7", port=5000) app.run()