Python-opencv學習第三十課：人臉檢測
文章目錄
- Python-opencv學習第三十課：人臉檢測
- 一、學習部分
- 二、代碼部分
- 1.引入庫
- 2.完整代碼
- 三、運行結果
- 總結
一、學習部分
記錄筆者學習Python-opencv學習第三十課：人臉檢測，代碼資料來源于網路賈老師視頻，
二、代碼部分
1.引入庫
代碼如下：
import cv2 as cv
import matplotlib.pyplot as plt
import numpy as np
2.完整代碼
代碼如下：
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
def read_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
# cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", image)
cv.waitKey(0)
cv.destroyAllWindows()
def color_space_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
hsv = cv.cvtColor(image, cv.COLOR_HSV2BGR) # H 0 ~180
# cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("gray", gray)
cv.imshow("hsv", hsv)
cv.waitKey(0)
cv.destroyAllWindows()
def mat_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
h,w,c = image.shape
roi = image[60:200, 60:280, :]
blank = np.zeros((h, w, c), dtype=np.uint8)
# blank[60:200, 60:280, :] = image[60:200, 60:280, :]
blank = image # np.copy(image)
cv.imshow("blank", blank)
cv.imshow("roi", roi)
cv.waitKey(0)
cv.destroyAllWindows()
def pixel_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
cv.imshow("input", image)
h,w,c = image.shape
for row in range(h):
for col in range(w):
b,g,r = image[row, col]
image[row, col] = (0, g, r)
cv.imshow("result", image)
cv.imwrite("D:/image_result.png", image)
cv.waitKey(0)
cv.destroyAllWindows()
def math_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
cv.imshow("input", image)
h,w,c = image.shape
blank = np.zeros_like(image)
blank[:,:] = (2, 2, 2)
cv.imshow("blank", blank)
result = cv.multiply(image, blank)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def nothing(x):
print(x)
def adjust_lightness_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.createTrackbar("lightness", "input", 0, 100, nothing)
cv.imshow("input", image)
blank = np.zeros_like(image)
while True:
pos = cv.getTrackbarPos("lightness", "input")
blank[:,:] = (pos, pos, pos)
# cv.imshow("blank", blank)
result = cv.add(image, blank)
cv.imshow("result", result)
c = cv.waitKey(1)
if c == 27:
break
cv.destroyAllWindows()
def adjust_contrast_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.createTrackbar("lightness", "input", 0, 100, nothing)
cv.createTrackbar("contrast", "input", 100, 200, nothing)
cv.imshow("input", image)
blank = np.zeros_like(image)
while True:
light = cv.getTrackbarPos("lightness", "input")
contrast = cv.getTrackbarPos("contrast", "input") / 100
print("light: ", light, "contrast: ", contrast)
result = cv.addWeighted(image, contrast, blank, 0.5, light)
cv.imshow("result", result)
c = cv.waitKey(1)
if c == 27:
break
cv.destroyAllWindows()
def keys_demo():
image = cv.imread("D:/images/test.png") # BGR, 0~255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", image)
while True:
c = cv.waitKey(1)
if c == 49: #1
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
cv.imshow("result", gray)
if c == 50: #2
hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
cv.imshow("result", hsv)
if c == 51: # 3
invert = cv.bitwise_not(image)
cv.imshow("result", invert)
if c == 27:
break
cv.destroyAllWindows()
def color_table_demo():
colormap = [
cv.COLORMAP_AUTUMN,
cv.COLORMAP_BONE,
cv.COLORMAP_JET,
cv.COLORMAP_WINTER,
cv.COLORMAP_RAINBOW,
cv.COLORMAP_OCEAN,
cv.COLORMAP_SUMMER,
cv.COLORMAP_SPRING,
cv.COLORMAP_COOL,
cv.COLORMAP_PINK,
cv.COLORMAP_HOT,
cv.COLORMAP_PARULA,
cv.COLORMAP_MAGMA,
cv.COLORMAP_INFERNO,
cv.COLORMAP_PLASMA,
cv.COLORMAP_VIRIDIS,
cv.COLORMAP_CIVIDIS,
cv.COLORMAP_TWILIGHT,
cv.COLORMAP_TWILIGHT_SHIFTED ]
image = cv.imread("D:/images/canjian.jpg") # BGR, 0~255
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", image)
index = 0
while True:
dst = cv.applyColorMap(image, colormap[index%19])
index += 1
cv.imshow("color style", dst);
c = cv.waitKey(400)
if c == 27:
break
cv.destroyAllWindows()
def bitwise_demo():
b1 = np.zeros((400, 400, 3), dtype=np.uint8)
b1[:,:] = (255, 0, 255)
b2 = np.zeros((400, 400, 3), dtype=np.uint8)
b2[:,:] = (0, 255, 255)
cv.imshow("b1", b1);
cv.imshow("b2", b2);
dst1 = cv.bitwise_and(b1, b2)
dst2 = cv.bitwise_or(b1, b2)
cv.imshow("bitwise_and", dst1)
cv.imshow("bitwise_or", dst2)
cv.waitKey(0)
cv.destroyAllWindows()
def channels_split_demo():
b1 = cv.imread("D:/images/lena.jpg")
print(b1.shape)
cv.imshow("input", b1)
cv.imshow("b1", b1[:,:,2])
mv = cv.split(b1)
mv[0][:,:] = 255
result = cv.merge(mv)
dst = np.zeros(b1.shape, dtype=np.uint8)
cv.mixChannels([b1], [dst], fromTo=[2, 0, 1, 1, 0, 2])
cv.imshow("output4", dst)
cv.imshow("result",result)
cv.waitKey(0)
cv.destroyAllWindows()
def color_space_demo():
b1 = cv.imread("D:/images/greenback.png")
print(b1.shape)
cv.imshow("input", b1)
hsv = cv.cvtColor(b1, cv.COLOR_BGR2HSV)
cv.imshow("hsv", hsv)
mask = cv.inRange(hsv, (35, 43, 46), (77, 255, 255))
cv.bitwise_not(mask, mask)
result = cv.bitwise_and(b1, b1, mask=mask)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def pixel_stat_demo():
b1 = cv.imread("D:/images/1024.png")
print(b1.shape)
cv.imshow("input", b1)
print(np.max(b1[:,:,2]))
means, dev = cv.meanStdDev(b1)
print(means, "dev: ", dev)
cv.waitKey(0)
cv.destroyAllWindows()
def drawing_demo():
b1 = cv.imread("D:/images/1024.png")#np.zeros((512, 512, 3), dtype=np.uint8)
temp = np.copy(b1)
cv.rectangle(b1, (50, 50), (400, 400), (0, 0, 255), 4, 8, 0)
# cv.circle(b1, (200, 200), 100, (255, 0, 0), -1, 8, 0)
# cv.line(b1, (50, 50), (400, 400), (0, 255, 0), 4, 8, 0)
cv.putText(b1, "99% face", (50, 50), cv.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 255), 2, 8)
cv.imshow("input", b1)
cv.waitKey(0)
cv.destroyAllWindows()
def random_color_demo():
b1 = np.zeros((512, 512, 3), dtype=np.uint8)
while True:
xx = np.random.randint(0, 512, 2, dtype=np.int)
yy = np.random.randint(0, 512, 2, dtype=np.int)
bgr = np.random.randint(0, 255, 3, dtype=np.int32)
print(bgr[0], bgr[1], bgr[2])
cv.line(b1, (xx[0], yy[0]), (xx[1], yy[1]), (np.int(bgr[0]), np.int(bgr[1]), np.int(bgr[2])), 1, 8, 0)
cv.imshow("input", b1)
c = cv.waitKey(10)
if c == 27:
break
cv.destroyAllWindows()
def polyline_drawing_demo():
canvas = np.zeros((512, 512, 3), dtype=np.uint8)
pts = np.array([[100, 100], [350, 100], [450, 280], [320, 450], [80, 400]], dtype=np.int32)
# cv.fillPoly(canvas, [pts], (255, 0, 255), 8, 0);
# cv.polylines(canvas, [pts], True, (0, 0, 255), 2, 8, 0);
cv.drawContours(canvas, [pts], -1, (255, 0, 0), -1);
cv.imshow("polyline", canvas);
cv.waitKey(0)
cv.destroyAllWindows()
b1 = cv.imread("D:/images/1024.png") # np.zeros((512, 512, 3), dtype=np.uint8)
img = np.copy(b1)
x1 = -1
x2 = -1
y1 = -1
y2 = -1
def mouse_drawing(event, x, y, flags, param):
global x1, y1, x2, y2
if event == cv.EVENT_LBUTTONDOWN:
x1 = x
y1 = y
if event == cv.EVENT_MOUSEMOVE:
if x1 < 0 or y1 < 0:
return
x2 = x
y2 = y
dx = x2 - x1
dy = y2 - y1
if dx > 0 and dy > 0:
b1[:,:,:] = img[:,:,:]
cv.rectangle(b1, (x1, y1), (x2, y2), (0, 0, 255), 2, 8, 0)
if event == cv.EVENT_LBUTTONUP:
x2 = x
y2 = y
dx = x2 - x1
dy = y2 - y1
if dx > 0 and dy > 0:
b1[:, :, :] = img[:,:,:]
cv.rectangle(b1, (x1, y1), (x2, y2), (0, 0, 255), 2, 8, 0)
x1 = -1
x2 = -1
y1 = -1
y2 = -1
def mouse_demo():
cv.namedWindow("mouse_demo", cv.WINDOW_AUTOSIZE)
cv.setMouseCallback("mouse_demo", mouse_drawing)
while True:
cv.imshow("mouse_demo", b1)
c = cv.waitKey(10)
if c == 27:
break
cv.destroyAllWindows()
def norm_demo():
image = cv.imread("D:/images/1024.png")
cv.namedWindow("norm_demo", cv.WINDOW_AUTOSIZE)
result = np.zeros_like(np.float32(image))
cv.normalize(np.float32(image), result, 0, 1, cv.NORM_MINMAX, dtype=cv.CV_32F)
cv.imshow("norm_demo", np.uint8(result*255))
cv.waitKey(0)
cv.destroyAllWindows()
def resize_demo():
image = cv.imread("D:/images/1024.png")
h, w, c = image.shape
cv.namedWindow("resize", cv.WINDOW_AUTOSIZE)
dst = cv.resize(image, (0, 0), fx=0.75, fy=0.75, interpolation=cv.INTER_NEAREST)
cv.imshow("resize", dst)
cv.waitKey(0)
cv.destroyAllWindows()
def flip_demo():
image = cv.imread("D:/images/1024.png")
cv.imshow("input", image)
cv.namedWindow("flip", cv.WINDOW_AUTOSIZE)
dst = cv.flip(image, -1)
cv.imshow("flip", dst)
cv.waitKey(0)
cv.destroyAllWindows()
def rotate_demo():
src = cv.imread("D:/images/dannis1.png")
cv.imshow("input", src)
h, w, c = src.shape
M = np.zeros((2, 3), dtype=np.float32)
alpha = np.cos(np.pi / 4.0)
beta = np.sin(np.pi / 4.0)
print("alpha : ", alpha)
# 初始旋轉矩陣
M[0, 0] = alpha
M[1, 1] = alpha
M[0, 1] = beta
M[1, 0] = -beta
cx = w / 2
cy = h / 2
tx = (1 - alpha) * cx - beta * cy
ty = beta * cx + (1 - alpha) * cy
M[0, 2] = tx
M[1, 2] = ty
# change with full size
bound_w = int(h * np.abs(beta) + w * np.abs(alpha))
bound_h = int(h * np.abs(alpha) + w * np.abs(beta))
# 添加中心位置遷移
M[0, 2] += bound_w / 2 - cx
M[1, 2] += bound_h / 2 - cy
dst = cv.warpAffine(src, M, (bound_w, bound_h))
cv.imshow("rotate without cropping", dst)
cv.waitKey(0)
cv.destroyAllWindows()
def video_demo():
cap = cv.VideoCapture("D:/images/video/dushuhu.mp4")
w = cap.get(cv.CAP_PROP_FRAME_WIDTH)
h = cap.get(cv.CAP_PROP_FRAME_HEIGHT)
fps = cap.get(cv.CAP_PROP_FPS)
out = cv.VideoWriter("D:/test.mp4", cv.CAP_ANY, np.int(cap.get(cv.CAP_PROP_FOURCC)), fps, (np.int(w), np.int(h)), True)
print(w, h, fps)
while True:
ret, frame = cap.read()
if ret is not True:
break
cv.imshow("frame", frame)
hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
cv.imshow("result", hsv)
out.write(hsv)
c = cv.waitKey(10)
if c == 27:
break
cv.destroyAllWindows()
out.release()
cap.release()
def image_hist():
image = cv.imread("D:/images/dannis1.png")
cv.imshow("input", image)
color = ('blue', 'green', 'red')
for i, color in enumerate(color):
hist = cv.calcHist([image], [i], None, [32], [0, 256])
print(hist)
plt.plot(hist, color=color)
plt.xlim([0, 32])
plt.show()
cv.waitKey(0)
cv.destroyAllWindows()
def hist2d_demo():
image = cv.imread("D:/images/dannis1.png")
hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
hist = cv.calcHist([hsv], [0, 1], None, [48, 48], [0, 180, 0, 256])
dst = cv.resize(hist, (400, 400))
cv.normalize(dst, dst, 0, 255, cv.NORM_MINMAX)
cv.imshow("image", image)
dst = cv.applyColorMap(np.uint8(dst), cv.COLORMAP_JET)
cv.imshow("hist", dst)
plt.imshow(hist, interpolation='nearest')
plt.title("2D Histogram")
plt.show()
cv.waitKey(0)
cv.destroyAllWindows()
def eqhist_demo():
image = cv.imread("D:/images/cat.jpg", cv.IMREAD_GRAYSCALE)
cv.imshow("input", image)
result = cv.equalizeHist(image)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def blur_demo():
image = cv.imread("D:/images/cat.jpg")
cv.imshow("input", image)
result = cv.blur(image, (15, 15))
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def conv_demo():
image = cv.imread("D:/images/cat.jpg")
cv.imshow("input", image)
result = cv.GaussianBlur(image, (0, 0), 15)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
def bifilter_demo():
image = cv.imread("D:/images/example.png")
cv.imshow("input", image)
result = cv.bilateralFilter(image, 0, 100, 10)
cv.imshow("result", result)
cv.waitKey(0)
cv.destroyAllWindows()
model_bin = "E:/python/opencv/opencv_face_detector_uint8.pb"
config_text = "E:/python/opencv/opencv_face_detector.pbtxt";
def face_detection_demo():
net = cv.dnn.readNetFromTensorflow(model=model_bin, config=config_text)
cap = cv.VideoCapture("C:/Users/akaak/Videos/01.mp4")
while True:
ret, frame = cap.read()
h, w, c = frame.shape
if ret is not True:
break
# NCHW
blob = cv.dnn.blobFromImage(frame, 1.0, (300, 300), (104.0, 177.0, 123.0), False, False)
net.setInput(blob)
outs = net.forward() # 1x1xNx7
for detection in outs[0, 0, :, :]:
score = float(detection[2])
if score > 0.5:
left = detection[3] * w
top = detection[4] * h
right = detection[5] * w
bottom = detection[6] * h
cv.rectangle(frame, (np.int(left), np.int(top)), (np.int(right), np.int(bottom)), (0, 0, 255), 2, 8, 0)
cv.imshow("frame", frame)
c = cv.waitKey(1)
if c == 27:
break
cv.destroyAllWindows()
cap.release()
if __name__ == "__main__":
face_detection_demo()
face_detector代碼如下：
import cv2 as cv
model_bin = "E:/python/opencv/opencv_face_detector_uint8.pb"
config_text = "E:/python/opencv/opencv_face_detector.pbtxt";
def video_detection():
# load tensorflow model
net = cv.dnn.readNetFromTensorflow(model_bin, config=config_text)
capture = cv.VideoCapture("C:/Users/akaak/Videos/01.mp4")
# 人臉檢測
while True:
e1 = cv.getTickCount()
ret, frame = capture.read()
if ret is not True:
break
h, w, c = frame.shape
blobImage = cv.dnn.blobFromImage(frame, 1.0, (300, 300), (104.0, 177.0, 123.0), False, False);
net.setInput(blobImage)
cvOut = net.forward()
# Put efficiency information.
t, _ = net.getPerfProfile()
label = 'Inference time: %.2f ms' % (t * 1000.0 / cv.getTickFrequency())
# 繪制檢測矩形
for detection in cvOut[0,0,:,:]:
score = float(detection[2])
objIndex = int(detection[1])
if score > 0.5:
left = detection[3]*w
top = detection[4]*h
right = detection[5]*w
bottom = detection[6]*h
# 繪制
cv.rectangle(frame, (int(left), int(top)), (int(right), int(bottom)), (255, 0, 0), thickness=2)
cv.putText(frame, "score:%.2f"%score, (int(left), int(top)), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1)
e2 = cv.getTickCount()
fps = cv.getTickFrequency() / (e2 - e1)
cv.putText(frame, label + (" FPS: %.2f"%fps), (10, 50), cv.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255), 2)
cv.imshow('face-detection-demo', frame)
c = cv.waitKey(1)
if c == 27:
break
cv.destroyAllWindows()
if __name__ == "__main__":
video_detection()
三、運行結果
總結
本文介紹了筆者學習Python-opencv第三十課：人臉識別，感謝bilibili賈老師的視頻，完成了大作業一部分任務，giao！（代碼資料來源于網路賈老師視頻）
轉載請註明出處，本文鏈接：https://www.uj5u.com/qita/347232.html
標籤：其他