From d8f9f984fcf8684e110a87678158cad9252559ea Mon Sep 17 00:00:00 2001
From: jkunimune15 <jkunimune15@punahou.edu>
Date: Mon, 14 Mar 2016 19:04:04 -0400
Subject: [PATCH] Turning in my computer vision toolbox

---
 .face_detect.py.swp             |   Bin 0 -> 12288 bytes
 deface_video.py                 |    29 +
 face_detect.py                  |    30 +-
 haarcascade_frontalface_alt.xml | 24350 ++++++++++++++++++++++++++++++
 input.mp3                       |   Bin 0 -> 1629360 bytes
 5 files changed, 24406 insertions(+), 3 deletions(-)
 create mode 100644 .face_detect.py.swp
 create mode 100644 deface_video.py
 create mode 100644 haarcascade_frontalface_alt.xml
 create mode 100644 input.mp3

diff --git a/.face_detect.py.swp b/.face_detect.py.swp
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diff --git a/deface_video.py b/deface_video.py
new file mode 100644
index 0000000..75738b0
--- /dev/null
+++ b/deface_video.py
@@ -0,0 +1,29 @@
+import numpy as np
+import cv2
+
+#cap = cv2.VideoCapture(0)
+cap = cv2.VideoCapture('/home/jkunimune/ToolBox-ComputerVision/input.mp3')
+kernel = np.ones((21,21),'uint8')
+face_cascade = cv2.CascadeClassifier('/home/jkunimune/ToolBox-ComputerVision/haarcascade_frontalface_alt.xml')
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+while(True):
+    # Capture frame-by-frame
+    ret, frame = cap.read()
+    frame = cv2.flip(frame,1)   # makes image face the right way
+    faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20,20))
+    for (x,y,w,h) in faces:
+        frame[y:y+h,x:x+w,:] = cv2.dilate(frame[y:y+h,x:x+w,:], kernel)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/2,h/2), 0,0,360, (0,255,255), thickness=-1)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/2,h/2), 0,0,360, (0,0,0), thickness=3)
+        cv2.line(frame, (x+w/3,y+h/4), (x+w/3,y+h/2), (0,0,0), thickness=3)
+        cv2.line(frame, (x+2*w/3,y+h/4), (x+2*w/3,y+h/2), (0,0,0), thickness=3)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/3,h/3), 0,0,180, (0,0,0), thickness=3)
+     # Display the resulting frame
+    #cv2.imshow('frame',frame)
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/face_detect.py b/face_detect.py
index 247a4d1..303a77f 100644
--- a/face_detect.py
+++ b/face_detect.py
@@ -1,4 +1,28 @@
-""" Experiment with face detection and image filtering using OpenCV """
-
+import numpy as np
 import cv2
-import numpy as np
\ No newline at end of file
+
+cap = cv2.VideoCapture(0)
+kernel = np.ones((21,21),'uint8')
+face_cascade = cv2.CascadeClassifier('/home/jkunimune/ToolBox-ComputerVision/haarcascade_frontalface_alt.xml')
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+while(True):
+    # Capture frame-by-frame
+    ret, frame = cap.read()
+    frame = cv2.flip(frame,1)   # makes image face the right way
+    faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20,20))
+    for (x,y,w,h) in faces:
+        frame[y:y+h,x:x+w,:] = cv2.dilate(frame[y:y+h,x:x+w,:], kernel)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/2,h/2), 0,0,360, (0,255,255), thickness=-1)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/2,h/2), 0,0,360, (0,0,0), thickness=3)
+        cv2.line(frame, (x+w/3,y+h/4), (x+w/3,y+h/2), (0,0,0), thickness=3)
+        cv2.line(frame, (x+2*w/3,y+h/4), (x+2*w/3,y+h/2), (0,0,0), thickness=3)
+        cv2.ellipse(frame, (x+w/2,y+h/2), (w/3,h/3), 0,0,180, (0,0,0), thickness=3)
+     # Display the resulting frame
+    cv2.imshow('frame',frame)
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/haarcascade_frontalface_alt.xml b/haarcascade_frontalface_alt.xml
new file mode 100644
index 0000000..ade4b21
--- /dev/null
+++ b/haarcascade_frontalface_alt.xml
@@ -0,0 +1,24350 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 20x20 gentle adaboost frontal face detector.
+    Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<cascade type_id="opencv-cascade-classifier"><stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>20</height>
+  <width>20</width>
+  <stageParams>
+    <maxWeakCount>213</maxWeakCount></stageParams>
+  <featureParams>
+    <maxCatCount>0</maxCatCount></featureParams>
+  <stageNum>22</stageNum>
+  <stages>
+    <_>
+      <maxWeakCount>3</maxWeakCount>
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