eye完善，grabcut功能提交

faceai/eye.py

@@ -30,16 +30,23 @@
 
 #获取眼球中心
 def houghCircles(path, counter):
-    img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
+    img = cv2.imread(path, 0)
     # img = cv2.medianBlur(img, 5)
 
+    x = cv2.Sobel(img, -1, 1, 0, ksize=3)
+    y = cv2.Sobel(img, -1, 0, 1, ksize=3)
+    absx = cv2.convertScaleAbs(x)
+    absy = cv2.convertScaleAbs(y)
+    img = cv2.addWeighted(absx, 0.5, absy, 0.5, 0)
+
     # ycrcb = cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB)
     # channels = cv2.split(ycrcb)
     # cv2.equalizeHist(channels[0], channels[0])  #输入通道、输出通道矩阵
     # cv2.merge(channels, ycrcb)  #合并结果通道
     # cv2.cvtColor(ycrcb, cv2.COLOR_YCR_CB2BGR, img)
 
     # img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
     cimg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
 
     # cv2.imshow("img2", img)
@@ -50,9 +57,9 @@ def houghCircles(path, counter):
         cv2.HOUGH_GRADIENT,
         1,
         50,
-        param1=50 / 2,
-        param2=30 / 2,
-        minRadius=0,
+        param1=50,
+        param2=10,
+        minRadius=2,
         maxRadius=0)
 
     circles = np.uint16(np.around(circles))
@@ -62,7 +69,7 @@ def houghCircles(path, counter):
         # draw the center of the circle
         cv2.circle(cimg, (i[0], i[1]), 2, (0, 0, 255), 2)
     # cv2.imshow("img" + str(counter), cimg)
-    return (i[0], i[1])
+    return (i[0] + 3, i[1] + 3)
 
 
 #彩色直方图均衡化
@@ -83,22 +90,22 @@ def hist(img):
 def discern(img, counter):
     grayImg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     color = (0, 255, 0)
-    # 调用识别人脸
     faceRects = classifier.detectMultiScale(
         grayImg, scaleFactor=1.2, minNeighbors=3, minSize=(58, 58))
     if len(faceRects):
         for faceRect in faceRects:
             x, y, w, h = faceRect
             rightEyeImg = img[(y):(y + h), (x):(x + w)]
-            cv2.rectangle(img, (x, y), (x + h, y + w), color, 2)
-
-            cv2.imwrite("img/temp.png", hist(rightEyeImg))
+            # cv2.rectangle(img, (x, y), (x + h, y + w), color, 2)
+            rightEyeImg = cv2.GaussianBlur(rightEyeImg, (5, 5), 1)
+            # rightEyeImg = hist(rightEyeImg)
+            cv2.imwrite("img/temp.png", rightEyeImg)
+            # cv2.imwrite("img/temp.png", rightEyeImg)
             circleCenter = houghCircles("img/temp.png", counter)  #(x,y)
             cv2.circle(img, (x + circleCenter[0], y + circleCenter[1]), 2,
-                       (0, 0, 255), 2)
+                       (128, 0, 0), 2)
             counter += 1
-
-    cv2.imshow("image", img)  # 显示图像
+        cv2.imshow("image", img)
 
 
 # path = "img/ag-3.png"
@@ -116,18 +123,18 @@ def discern(img, counter):
 #         counter += 1
 #         # cv2.imshow("img", houghCircles("img/temp.png"))
 
-path = "img/ag-3.png"
+path = "img/ag.png"
 img = cv2.imread(path)
 discern(img, counter)
 
-cap = cv2.VideoCapture(0)
-while (1):
-    ret, frame = cap.read()
+# cap = cv2.VideoCapture(0)
+# while (1):
+#     ret, frame = cap.read()
 
-    # cv2.imshow('frame', gray)
-    discern(frame, counter)
-    if cv2.waitKey(1) & 0xFF == ord('q'):
-        break
+#     # cv2.imshow('frame', gray)
+#     discern(frame, counter)
+#     if cv2.waitKey(1) & 0xFF == ord('q'):
+#         break
 
 #
 
@@ -177,5 +184,6 @@ def discern(img, counter):
 # time.sleep(1)
 
 # cv2.imshow('detected circles', cimg)
-# cv2.waitKey(0)
-# cv2.destroyAllWindows()
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

faceai/eye2.py

@@ -0,0 +1,88 @@
+import cv2
+import dlib
+import numpy as np
+import time
+
+classifier = cv2.CascadeClassifier(
+    "C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_eye_tree_eyeglasses.xml"  # haarcascade_eye
+)
+
+
+#彩色直方图均衡化
+def hist(img):
+    ycrcb = cv2.cvtColor(img, cv2.COLOR_BGR2YCR_CB)
+    channels = cv2.split(ycrcb)
+    cv2.equalizeHist(channels[0], channels[0])  #输入通道、输出通道矩阵
+    cv2.merge(channels, ycrcb)  #合并结果通道
+    cv2.cvtColor(ycrcb, cv2.COLOR_YCR_CB2BGR, img)
+    return img
+
+
+def discern(img):
+    grayImg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faceRects = classifier.detectMultiScale(
+        grayImg, scaleFactor=1.2, minNeighbors=3, minSize=(30, 30))
+    if len(faceRects):
+        for faceRect in faceRects:
+            x, y, w, h = faceRect
+            rightEyeImg = img[(y):(y + h), (x):(x + w)]
+            # cv2.rectangle(img, (x, y), (x + h, y + w), color, 2)
+            # rightEyeImg = hist(rightEyeImg)
+            rightEyeImg = cv2.GaussianBlur(rightEyeImg, (5, 5), 1)
+
+            cv2.imwrite("img/temp.png", rightEyeImg)
+            # cv2.imshow("img", rightEyeImg)
+    # print(len(faceRects))
+
+
+# discern(cv2.imread("img/ag-2.png"))
+
+img = cv2.imread("img/temp.png", 0)
+
+# img = cv2.GaussianBlur(img, (3, 3), 0)
+# img = cv2.Canny(img, 50, 150)
+img = cv2.bilateralFilter(img, 7, 50, 50)
+
+# x = cv2.Sobel(img, -1, 1, 0, ksize=3)
+# y = cv2.Sobel(img, -1, 0, 1, ksize=3)
+# absx = cv2.convertScaleAbs(x)
+# absy = cv2.convertScaleAbs(y)
+# dist = cv2.addWeighted(absx, 0.5, absy, 0.5, 0)
+
+# img = cv2.GaussianBlur(img, (5, 5), 1)
+
+# laplacian = cv2.Laplacian(img, -1, ksize=3)
+
+# laplacian = cv2.GaussianBlur(laplacian, (3, 3), 1)
+# laplacian = cv2.medianBlur(laplacian, 3)
+
+# img = dist
+
+# img = cv2.cvtColor(dist, cv2.COLOR_BGR2GRAY)
+
+cimg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)  # cv2.imread("img/temp.png")  #
+
+# cv2.imshow("img2", img)
+# cv2.imshow("grayimg", grayimg)
+
+circles = cv2.HoughCircles(
+    img,
+    cv2.HOUGH_GRADIENT,
+    1,
+    100,
+    param1=50,
+    param2=10,
+    minRadius=2,
+    maxRadius=0)
+
+circles = np.uint16(np.around(circles))
+
+for i in circles[0, :]:
+    # draw the outer circle
+    # cv2.circle(cimg, (i[0], i[1]), i[2], (0, 255, 0), 1)
+    # draw the center of the circle
+    cv2.circle(cimg, (i[0], i[1]), 2, (0, 0, 255), 2)
+cv2.imshow("img", cimg)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

faceai/grabCut.py

@@ -0,0 +1,22 @@
+#coding=utf-8
+#抠图
+
+import numpy as np
+import cv2
+from matplotlib import pyplot as plt
+
+img = cv2.imread('img/face_recognition/Gates.png')
+mask = np.zeros(img.shape[:2], np.uint8)
+bgdModel = np.zeros((1, 65), np.float64)
+fgdModel = np.zeros((1, 65), np.float64)
+rect = (0, 0, 505, 448)  #划定区域
+cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 5,
+            cv2.GC_INIT_WITH_RECT)  #函数返回值为mask,bgdModel,fgdModel
+mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')  #0和2做背景
+
+img = img * mask2[:, :, np.newaxis]  #使用蒙板来获取前景区域
+
+cv2.imshow('p', img)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()