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betabot-vision
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changes to face recognition script

James Peret 8 years ago
parent
99e640f749
commit
4a5ad5047e
2 changed files with 10 additions and 8 deletions
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  1. BIN
      .DS_Store
  2. 10 8
      face_recognizer_v3.py

BIN
.DS_Store
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+ 10 - 8
face_recognizer_v3.py
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@@ -16,7 +16,7 @@ os.system('sudo modprobe bcm2835-v4l2')
16 16 
 # Set the framerate ( not sure this does anything! )
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 #os.system('v4l2-ctl -p 4')
18 18
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-width, height = 320, 240
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+width, height = 740, 480
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 cap = cv2.VideoCapture()
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 cap.open(0)
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 cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH,  width)
 
@@ -68,7 +68,7 @@ def faceDetect(frame):
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         flags=cv2.cv.CV_HAAR_SCALE_IMAGE | cv2.cv.CV_HAAR_FIND_BIGGEST_OBJECT | cv2.cv.CV_HAAR_DO_ROUGH_SEARCH
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     )
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-    print "Found {0} faces!".format(len(faces))
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+
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     global last_image_faces
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     image_faces = []
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@@ -86,9 +86,9 @@ def faceDetect(frame):
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                 # Info = [center_x, center_y, time_since_last_check, user, score]
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                 center = [center_x, center_y, pos[2] + 1]
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-                print("Tracking face " + str(counter))
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+                #print("Tracking face " + str(counter))
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                 counter = counter + 1
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-                if center[2] > 6:
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+                if center[2] > 20 and w >= 60 :
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                     if start_x > 0 and start_y > 0:
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                         face_crop = frame[y:(y+h), x:(x+w)]
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                         info = recognizeFace(face_crop)
 
@@ -100,8 +100,9 @@ def faceDetect(frame):
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                 if len(pos) > 3:
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                     center.append(pos[3])
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                     center.append(pos[4])
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-                    if pos[4] < 2000:
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+                    if pos[4] < 2500 or pos[4] > 7000:
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                         cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)
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+                        cv2.putText(frame, users[center[3]], (x, (y + h + 15)), font, 1, (0,0,255), 1, 1)
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                         cv2.putText(frame, "%.1f" % (center[4]/1000), ((x + w - 38), (y + 17)), font, 1, (0,0,255), 1, 1)
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                     else:
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                         cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
 
@@ -115,12 +116,13 @@ def faceDetect(frame):
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             center = [center_x, center_y, 1]
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             image_faces.append(center)
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             cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 255, 255), 2)
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-    print("Number of faces detected " + str(len(last_image_faces)))
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+    #print("Found " + str(len(faces)) + " faces | Recognized " + str(len(last_image_faces)) + " faces")
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+
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     last_image_faces = image_faces
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     return frame
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 def recognizeFace(face):
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-    print("Searching Face database...")
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+    #print("Searching Face database...")
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     match_found = False
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     face = cv2.resize(face, (120, 120))
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     face = cv2.cvtColor(face, cv2.cv.CV_BGR2GRAY)
 
@@ -130,7 +132,7 @@ def recognizeFace(face):
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     predicted_label = predict_image_from_model(model, face)
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     print 'Predicted: %(predicted)s  ' %  {"predicted": users[predicted_label[0]]}
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     print str(predicted_label[0]) + " - " + str(predicted_label[1])
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-    print c.face_recognized(users[predicted_label[0]])
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+    #print c.face_recognized(users[predicted_label[0]])
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     return predicted_label
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136 138 
 def loadFaceDB():