From 6d7bba285459ec085128b785dc6ff3c69a0407b6 Mon Sep 17 00:00:00 2001
From: Dhruv Dhayal <137479629+BlockNotes-4515@users.noreply.github.com>
Date: Sat, 13 Jul 2024 15:54:17 +0530
Subject: [PATCH] =?UTF-8?q?Day-8=5FSUMMER=5FTRAINING=5FK-MEANS/IMAGE/VEDIO?=
 =?UTF-8?q?.=20=F0=9F=98=8E=F0=9F=98=8D?=
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---
 Day-8 Face Label Real-Time (H.W).py | 42 +++++++++++++++++++++++++++++
 Day-8 Face Recognizatins (H.W).py   | 42 +++++++++++++++++++++++++++++
 2 files changed, 84 insertions(+)
 create mode 100644 Day-8 Face Label Real-Time (H.W).py
 create mode 100644 Day-8 Face Recognizatins (H.W).py

diff --git a/Day-8 Face Label Real-Time (H.W).py b/Day-8 Face Label Real-Time (H.W).py
new file mode 100644
index 0000000..736ebe4
--- /dev/null
+++ b/Day-8 Face Label Real-Time (H.W).py	
@@ -0,0 +1,42 @@
+import joblib;
+import cv2 ;
+import numpy as np;
+import matplotlib.pyplot as plt;
+
+cam = cv2.VideoCapture(1)
+path = "C:\\AIML\\datafiles\\haarcascade_frontalface_default (Practice).xml";
+# face detector .
+face_detector = cv2.CascadeClassifier(path).
+
+model_path = 'C:\\AIML\datafiles\\orl_face_model_2.xml';
+face_model = joblib.load(model_path);
+
+frame=True;
+count = 0;
+while(frame):
+    ret,im = cam.read();
+    im_new = cv2.resize(im, (512,512));
+
+    # covert the color (BGR) into grayscale
+    gray_im = cv2.cvtColor(im_new,cv2.COLOR_BGR2GRAY);
+
+    # run your classifier on the image.
+    faces = face_detector.detectMultiScale(gray_im,scaleFactor=1.1,minNeighbors=10);
+
+    # disply the bounding box on all the faces.
+    for (dx,dy,w,h) in faces:
+        cv2.rectangle(im_new, (dx,dy),(dx+w,dy+h),(0,0,255),2);
+        cropped_im = cv2.resize((gray_im[dy-20:(dy+h)+40,dx:(dx+w)]),(92,112));
+        lb = face_model.predict((cropped_im.reshape(1,-1)));
+        cv2.putText(im_new,'user: '+str(lb[0]),(dx-5,dy-5),cv2.FONT_HERSHEY_SIMPLEX,1,color=(255,0,0),thickness=2)
+
+
+    cv2.imshow('camera live feed', im_new)
+    # desired button of your choice .
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        frame=False;
+        break;
+  
+
+cam.release();
+cv2.destroyAllWindows();
\ No newline at end of file
diff --git a/Day-8 Face Recognizatins (H.W).py b/Day-8 Face Recognizatins (H.W).py
new file mode 100644
index 0000000..f562474
--- /dev/null
+++ b/Day-8 Face Recognizatins (H.W).py	
@@ -0,0 +1,42 @@
+import joblib;
+import cv2 ;
+import numpy as np;
+import matplotlib.pyplot as plt;
+
+cam = cv2.VideoCapture(1)
+path = "C:\\AIML\\datafiles\\haarcascade_frontalface_default (Practice).xml";
+# face detector 
+face_detector = cv2.CascadeClassifier(path);
+
+model_path = 'C:\\AIML\\datafiles\orl_face_model_2.xml';
+face_model = joblib.load(model_path);
+
+frame=True;
+count = 0;
+while(frame):
+    ret,im = cam.read();
+    im_new = cv2.resize(im, (512,512));
+
+    # covert the color (BGR) into grayscale.
+    gray_im = cv2.cvtColor(im_new,cv2.COLOR_BGR2GRAY);
+
+    # run your classifier on the image.
+    faces = face_detector.detectMultiScale(gray_im,scaleFactor=1.1,minNeighbors=10);
+
+    # disply the bounding box on all the faces.
+    for (dx,dy,w,h) in faces:
+        cv2.rectangle(im_new, (dx,dy),(dx+w,dy+h),(0,0,255),2)
+        cropped_im = cv2.resize((gray_im[dy-20:(dy+h)+40,dx:(dx+w)]),(92,112)) #Convert in PNG Image format of (112*92);
+        lb = face_model.predict((cropped_im.reshape(1,-1)))
+        cv2.putText(im_new,'user: '+str(lb[0]),(dx-5,dy-5),cv2.FONT_HERSHEY_SIMPLEX,1,color=(255,0,0),thickness=2)
+
+
+    cv2.imshow('Camera Live Feed', im_new)
+    # desired button of your choice .
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        frame=False;
+        break;
+  
+
+cam.release();
+cv2.destroyAllWindows();
\ No newline at end of file