get_example

# coding: utf-8

# In[2]:


from keras.models import load_model
from imutils import paths
import numpy as np
import imutils
import cv2
import pickle
import cv2
import win32api
import win32con
import time
import os
sample_nums = 0
minValue = 70
x0 = 400
y0 = 200
height = 200
width = 200
counter = 0
gestname = ""
path = ""
saveimg = False
def saveROIImg(img):
    global counter,saveimg,gestname,sample_nums
    if counter > sample_nums:
        saveimg = False
        counter = 0
        gestname = ""
        return 
    counter = counter + 1
    name = gestname + str(counter)
    print("Saving img:",name)
    cv2.imwrite(path+name + ".png", img)
    time.sleep(0.04 )
    


#肤色检测函数
def binaryMask(frame, x0, y0, width, height, framecount, plot ):
    cv2.rectangle(frame, (x0,y0),(x0+width,y0+height),(0,255,0),1)
    #roi = cv2.UMat(frame[y0:y0+height, x0:x0+width])
    roi = frame[y0:y0+height, x0:x0+width]
    gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray,(5,5),2)
    th3 = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY_INV,11,2)
    ret, res = cv2.threshold(th3, minValue, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
    if saveimg==True:
        saveROIImg(res)
    return res


font = cv2.FONT_HERSHEY_SIMPLEX
cap = cv2.VideoCapture(0)
cv2.namedWindow('Original', cv2.WINDOW_NORMAL)
# set rt size as 640x480
ret = cap.set(3,640)
ret = cap.set(4,480)
framecount = 0
fps = ""
start = time.time()
plot = np.zeros((512,512,3), np.uint8)
while(True):
    ret, frame = cap.read()
    frame = cv2.flip(frame, 3)
    frame = cv2.resize(frame, (640,480))   

    if ret == True:
        roi = binaryMask(frame, x0, y0, width, height, framecount, plot)    
        framecount = framecount + 1
        end  = time.time()
        timediff = (end - start)
        if( timediff >= 1):
            #timediff = end - start
            fps = 'FPS:%s' %(framecount)
            start = time.time()
            framecount = 0
    cv2.putText(frame,fps,(10,20), font, 0.7,(0,255,0),2,1)
    cv2.putText(frame,'push key c to create floder',(10,35), font, 0.7,(0,255,0),2,1)
    cv2.putText(frame,'push key s to save samples',(10,55), font, 0.7,(0,255,0),2,1)
    
    
    cv2.imshow('Original',frame)
    cv2.imshow('ROI', roi)
    key = cv2.waitKey(5) & 0xff
    #Esc键退出
    if key == 27:
        cap.release()
        cv2.destroyAllWindows()
    elif key == ord('c'):
        gestname = input("输入存放手势的文件夹名称: ")
        sample_nums = int(input("输入存放手势图片数目: "))
        try:
            os.makedirs(gestname)
        except OSError as e:
            print(gestname+'文件夹已创建')
        path = "./"+gestname+"/"
    elif key == ord('s'):
        if gestname=='':
            print("请先输入一个存放文件夹的名字")
        else:
            saveimg = True
    #手势识别框动态移动
    elif key == ord('i'):
        y0 = y0 - 5
    elif key == ord('k'):
        y0 = y0 + 5
    elif key == ord('j'):
        x0 = x0 - 5
    elif key == ord('l'):
        x0 = x0 + 5