used dnn model to incrase detector accuracy

Facial_Recognition_Software.py

@@ -7,21 +7,56 @@ from skimage import io
 
 #read test photo 
 pwd  =  sys.path[0]
-img = cv2.imread(pwd + "/Facial_test_images/photo2.jpg")
-
-color = (0, 255, 0)
+img = cv2.imread(pwd + "/Facial_test_images/6.jpg")
 
 grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
 
+resize_fx = 1
+resize_fy = 1
+
+grey = cv2.resize(grey, dsize=None, fx=resize_fx, fy=resize_fy, interpolation = cv2.INTER_AREA)
+
+
 classfier = cv2.CascadeClassifier(pwd + "/Facial_models/haarcascade_frontalface_alt2.xml")
 
-faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32)) 
+faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=1, minSize=(16, 16)) 
 
+color = (0, 255, 0)
 if len(faceRects) > 0:
     for faceRect in faceRects:
-        x, y, w, h = faceRect 
-        cv2.rectangle(img, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 3) 
+        x, y, w, h = faceRect
+        x = int(x/resize_fx)
+        y = int(y/resize_fy)
+        w = int(w/resize_fx)
+        h = int(h/resize_fy) 
+        cv2.rectangle(img, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 5) 
 
-cv2.imwrite('output.jpg',img) 
-cv2.imshow("face_image",img)
-cv2.waitKey(0)
+cv2.imwrite(pwd + "/Facial_test_images/output-a.jpg",img) 
+cv2.imshow("face_image_a",img)
+
+
+
+image =  cv2.imread(pwd + "/Facial_test_images/6.jpg")
+
+net = cv2.dnn.readNetFromCaffe(pwd+"/Facial_models/deploy.prototxt", pwd+"/Facial_models/res10_300x300_ssd_iter_140000_fp16.caffemodel")
+
+blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
+
+net.setInput(blob)
+
+detections = net.forward()
+
+h,w,c=image.shape
+for i in range(0, detections.shape[2]):
+    confidence = detections[0, 0, i, 2]
+    if confidence > 0.65:
+        box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
+        (startX, startY, endX, endY) = box.astype("int")
+        text = "{:.2f}%".format(confidence * 100)
+        y = startY - 10 if startY - 10 > 10 else startY + 10
+        cv2.rectangle(image, (startX, startY), (endX, endY),(0, 255,0), 5)
+        cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 1.00, (0, 255, 0), 3)
+
+cv2.imwrite(pwd + "/Facial_test_images/output-b.jpg", image) 
+cv2.imshow("face_image_b",image)
+cv2.waitKey(0)