Add files via upload

Author: tejaram15

database_connect.py

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+import sqlite3 as sql
+import cv2
+import numpy as np
+import sys
+import time
+from PIL import Image
+
+conn = sql.connect('test.db')
+c = conn.cursor()
+
+id = int(raw_input('Enter id: '))
+name = raw_input('Enter Name: ')
+age = int(raw_input('Enter age: '))
+
+#c.execute('CREATE TABLE Facedetails (id int PRIMARY KEY,name text,age int) ')
+c.execute("INSERT INTO Facedetails(id,name,age) VALUES(?,?,?)",(id,name,age))
+'''
+find = raw_input('Enter id to find : ')
+c = c.execute("SELECT * FROM Facedetails WHERE id = " + str(find))
+for row in c:
+    print 'Id = ',row[0]
+    print 'name = ',row[1]
+    print 'age = ',row[2]
+'''
+conn.commit()
+conn.close()
+
+print "Database Upated Successfully"

face_recog.py

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+import time
+import cv2
+import numpy as np
+import sys
+
+faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+cam = cv2.VideoCapture(0)
+ret,img = cam.read()
+
+name = raw_input('Enter user name for dataset')
+img_number = 0
+while True:
+    # Capture frame-by-frame
+    ret, img = cam.read()
+
+    t1=time.time()
+    
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+    faces = faceCascade.detectMultiScale(gray,scaleFactor=1.1,minNeighbors=5,minSize=(30, 30),flags=cv2.cv.CV_HAAR_SCALE_IMAGE
+    )
+
+    # Draw a rectangle around the faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+    # Display the resulting frame
+    cv2.imshow('Output', img)
+
+    print(time.time()-t1)
+
+    if(img_number > 20):
+          break
+    if cv2.waitKey(33) & 0xFF == 27:
+        break
+cam.release()
+cv2.destroyAllWindows()

face_recog_dataset_generator.py

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+import time
+import cv2
+import numpy as np
+import sys
+
+faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+cam = cv2.VideoCapture(0)
+ret,img = cam.read()
+
+id = raw_input('Enter your id')
+img_number = 0
+while True:
+    # Capture frame-by-frame
+    ret, img = cam.read()
+
+    t1=time.time()
+    
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+    faces = faceCascade.detectMultiScale(gray,scaleFactor=1.3,minNeighbors=5,minSize=(30, 30),flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
+
+    # Draw a rectangle around the faces
+    for (x, y, w, h) in faces:
+        img_number = img_number + 1
+        cv2.imwrite("dataset/{0}.{1}.jpg".format(str(id), str(img_number)), gray[y:y + h, x:x + w])
+        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+    # Display the resulting frame
+    cv2.imshow('Output', img)
+
+    print(time.time()-t1)
+
+    if(img_number > 200):
+          break
+    if cv2.waitKey(33) & 0xFF == 27:
+        break
+cam.release()
+cv2.destroyAllWindows()

face_recog_detector.py

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+import time
+import cv2
+import sqlite3 as sql
+import numpy as np
+import sys
+import os
+
+faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+cam = cv2.VideoCapture(0)
+rec = cv2.createLBPHFaceRecognizer()
+rec.load('trainingDataset.yml')
+id = 0
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+conn = sql.connect('test.db')
+c = conn.cursor()
+
+while True:
+    ret, img = cam.read()
+    t1=time.time()
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = faceCascade.detectMultiScale(gray,scaleFactor=1.3,minNeighbors=5,minSize=(30, 30),flags=cv2.cv.CV_HAAR_SCALE_IMAGE)
+    for (x, y, w, h) in faces:
+        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
+        id,conf = rec.predict(gray[y:y+h,x:x+w])
+        c = c.execute("SELECT * FROM Facedetails WHERE id = " + str(id))
+        for row in c:
+            cv2.putText(img, 'Id : '+str(row[0]), (x, y + h + 10), font, 0.5, (200, 255, 255), 1)
+            cv2.putText(img, 'Name : '+str(row[1]), (x, y + h + 25), font, 0.5, (200, 255, 255), 1)
+            cv2.putText(img, 'Age : '+str(row[2]), (x, y + h + 37), font, 0.5, (200, 255, 255), 1)
+            cv2.putText(img, 'conf : '+ str(conf), (x, y + h + 50), font, 0.5, (200, 255, 255), 1)
+    cv2.imshow('Output', img)
+    print(time.time()-t1)
+    if cv2.waitKey(33) & 0xFF == 27:
+        break
+cam.release()
+cv2.destroyAllWindows()

face_recog_trainer.py

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+import os
+import cv2
+import numpy as np
+from PIL import Image
+
+recognizer = cv2.createLBPHFaceRecognizer()
+path = 'dataset'
+strvar = 'dataset\\'
+
+
+def getimgid():
+    global path
+    imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
+
+    faceSamples = []
+    ids = []
+    for imagePath in imagePaths:
+        pilImage = Image.open(imagePath)
+        imageNp = np.array(pilImage, 'uint8')
+        id = int(imagePath.strip(strvar).strip('.jpg').split('.')[0])
+        faceSamples.append(imageNp)
+        ids.append(id)
+        cv2.imshow('training', imageNp)
+        cv2.waitKey(10)
+    return np.array(ids), faceSamples
+
+ids, faces = getimgid()
+recognizer.train(faces, ids)
+recognizer.save('trainingDataset.yml')
+cv2.destroyAllWindows()