import sys import platform import glob import cv2 import os from flask_cors import CORS 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__) CORS(app, supports_credentials=True, resources={r"/*": {"origins": "*"}}, headers=['Content-Type', 'Authorization']) threshold = 40 kernel = np.ones((5, 5), np.uint8) global status status="NOT" global isGoodFeatures isGoodFeatures="GOOD" orb = cv2.ORB_create(nfeatures=1000) 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') #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 TODAy' @app.route('/blogs') def blogs(): return 'Welcome1 to The Blog App_Updated_BYTES' @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 = request.files["image"] #decoded_img = base64.b64decode(json['firstName']) #img = Image.open(io.BytesIO(image.read())) img = Image.open(BytesIO(decoded_img.read())) #print("SANKARi") file_name = file_name_for_base64_data + ".jpg" #print(file_name) #img.save(file_name, "jpeg",quality=100) #np_data = np.frombuffer(decoded_img,np.uint8) #print("DE") #img21 = cv2.imdecode(np_data,cv2.IMREAD_UNCHANGED) img21 = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR) #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)>200: 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) #print(status) 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(addurlParent+"SA") #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="192.168.1.4", port=5000) app.run()