AI for Everyone LESSON 28: Storing and Loading Gesture Training Data in Mediapipe

In this video lesson we show how to train our model for different gestures, and how to store and load our training data. For your convenience, we include the code below we develop in this video.

import time
import cv2
print(cv2.__version__)
import numpy as np
import pickle

class mpHands:
    import mediapipe as mp
    def __init__(self,maxHands=2,tol1=.5,tol2=.5):
        self.hands=self.mp.solutions.hands.Hands(False,maxHands,tol1,tol2)
    def Marks(self,frame):
        myHands=[]
        frameRGB=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
        results=self.hands.process(frameRGB)
        if results.multi_hand_landmarks != None:
            for handLandMarks in results.multi_hand_landmarks:
                myHand=[]
                for landMark in handLandMarks.landmark:
                    myHand.append((int(landMark.x*width),int(landMark.y*height)))
                myHands.append(myHand)
        return myHands
def findDistances(handData):
    distMatrix=np.zeros([len(handData),len(handData)],dtype='float')
    palmSize=((handData[0][0]-handData[9][0])**2+(handData[0][1]-handData[9][1])**2)**(1./2.)
    for row in range(0,len(handData)):
        for column in range(0,len(handData)):
            distMatrix[row][column]=(((handData[row][0]-handData[column][0])**2+(handData[row][1]-handData[column][1])**2)**(1./2.))/palmSize
    return distMatrix

def findError(gestureMatrix,unknownMatrix,keyPoints):
    error=0
    for row in keyPoints:
        for column in keyPoints:
            error=error+abs(gestureMatrix[row][column]-unknownMatrix[row][column])
    print(error)
    return error
def findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol):
    errorArray=[]
    for i in range(0,len(gestNames),1):
        error=findError(knownGestures[i],unknownGesture,keyPoints)
        errorArray.append(error)
    errorMin=errorArray[0]
    minIndex=0
    for i in range(0,len(errorArray),1):
        if errorArray[i]<errorMin:
            errorMin=errorArray[i]
            minIndex=i
    if errorMin<tol:
        gesture=gestNames[minIndex]
    if errorMin>=tol:
        gesture='Unknown'
    return gesture


width=1280
height=720
cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)
cam.set(cv2.CAP_PROP_FPS, 30)
cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))
findHands=mpHands(1)
time.sleep(5)
keyPoints=[0,4,5,9,13,17,8,12,16,20]

train=int(input('Enter 1 to Train, Enter 0 to Recognize '))
if train==1:
    trainCnt=0
    knownGestures=[]
    numGest=int(input('How Many Gestures Do You Want? '))
    gestNames=[]
    for i in range(0,numGest,1):
        prompt='Name of Gesture #'+str(i+1)+' '
        name=input(prompt)
        gestNames.append(name)
    print(gestNames)
    trainName=input('Filename for training data? (Press Enter for Default) ')
    if trainName=='':
        trainName='default'
    trainName=trainName+'.pkl'
if train==0:
    trainName=input('What Training Data Do You Want to Use? (Press Enter for Default) ')
    if trainName=='':
        trainName='default'
    trainName=trainName+'.pkl'
    with open(trainName,'rb') as f:
        gestNames=pickle.load(f)
        knownGestures=pickle.load(f)

tol=10

while True:
    ignore,  frame = cam.read()
    frame=cv2.resize(frame,(width,height))
    handData=findHands.Marks(frame)
    if train==1:
        if handData!=[]:
            print('Please Show Gesture ',gestNames[trainCnt],': Press t when Ready')
            if cv2.waitKey(1) & 0xff==ord('t'):
                knownGesture=findDistances(handData[0])
                knownGestures.append(knownGesture)
                trainCnt=trainCnt+1
                if trainCnt==numGest:
                    train=0
                    with open(trainName,'wb') as f:
                        pickle.dump(gestNames,f)
                        pickle.dump(knownGestures,f)
    if train == 0:
        if handData!=[]:
            unknownGesture=findDistances(handData[0])
            myGesture=findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol)
            #error=findError(knownGesture,unknownGesture,keyPoints)
            cv2.putText(frame,myGesture,(100,175),cv2.FONT_HERSHEY_SIMPLEX,3,(255,0,0),8)
    for hand in handData:
        for ind in keyPoints:
            cv2.circle(frame,hand[ind],25,(255,0,255),3)
    cv2.imshow('my WEBcam', frame)
    cv2.moveWindow('my WEBcam',0,0)
    if cv2.waitKey(1) & 0xff ==ord('q'):
        break
cam.release()

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import time

import cv2

print(cv2.__version__)

import numpy as np

import pickle

class mpHands:

import mediapipe as mp

def __init__(self,maxHands=2,tol1=.5,tol2=.5):

self.hands=self.mp.solutions.hands.Hands(False,maxHands,tol1,tol2)

def Marks(self,frame):

myHands=[]

frameRGB=cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)

results=self.hands.process(frameRGB)

if results.multi_hand_landmarks != None:

for handLandMarks in results.multi_hand_landmarks:

myHand=[]

for landMark in handLandMarks.landmark:

myHand.append((int(landMark.x*width),int(landMark.y*height)))

myHands.append(myHand)

return myHands

def findDistances(handData):

distMatrix=np.zeros([len(handData),len(handData)],dtype='float')

palmSize=((handData[0][0]-handData[9][0])**2+(handData[0][1]-handData[9][1])**2)**(1./2.)

for row in range(0,len(handData)):

for column in range(0,len(handData)):

distMatrix[row][column]=(((handData[row][0]-handData[column][0])**2+(handData[row][1]-handData[column][1])**2)**(1./2.))/palmSize

return distMatrix

def findError(gestureMatrix,unknownMatrix,keyPoints):

error=0

for row in keyPoints:

for column in keyPoints:

error=error+abs(gestureMatrix[row][column]-unknownMatrix[row][column])

print(error)

return error

def findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol):

errorArray=[]

for i in range(0,len(gestNames),1):

error=findError(knownGestures[i],unknownGesture,keyPoints)

errorArray.append(error)

errorMin=errorArray[0]

minIndex=0

for i in range(0,len(errorArray),1):

if errorArray[i]<errorMin:

errorMin=errorArray[i]

minIndex=i

if errorMin<tol:

gesture=gestNames[minIndex]

if errorMin>=tol:

gesture='Unknown'

return gesture

width=1280

height=720

cam=cv2.VideoCapture(0,cv2.CAP_DSHOW)

cam.set(cv2.CAP_PROP_FRAME_WIDTH, width)

cam.set(cv2.CAP_PROP_FRAME_HEIGHT,height)

cam.set(cv2.CAP_PROP_FPS, 30)

cam.set(cv2.CAP_PROP_FOURCC,cv2.VideoWriter_fourcc(*'MJPG'))

findHands=mpHands(1)

time.sleep(5)

keyPoints=[0,4,5,9,13,17,8,12,16,20]

train=int(input('Enter 1 to Train, Enter 0 to Recognize '))

if train==1:

trainCnt=0

knownGestures=[]

numGest=int(input('How Many Gestures Do You Want? '))

gestNames=[]

for i in range(0,numGest,1):

prompt='Name of Gesture #'+str(i+1)+' '

name=input(prompt)

gestNames.append(name)

print(gestNames)

trainName=input('Filename for training data? (Press Enter for Default) ')

if trainName=='':

trainName='default'

trainName=trainName+'.pkl'

if train==0:

trainName=input('What Training Data Do You Want to Use? (Press Enter for Default) ')

if trainName=='':

trainName='default'

trainName=trainName+'.pkl'

with open(trainName,'rb') as f:

gestNames=pickle.load(f)

knownGestures=pickle.load(f)

tol=10

while True:

ignore, frame = cam.read()

frame=cv2.resize(frame,(width,height))

handData=findHands.Marks(frame)

if train==1:

if handData!=[]:

print('Please Show Gesture ',gestNames[trainCnt],': Press t when Ready')

if cv2.waitKey(1) & 0xff==ord('t'):

knownGesture=findDistances(handData[0])

knownGestures.append(knownGesture)

trainCnt=trainCnt+1

if trainCnt==numGest:

train=0

with open(trainName,'wb') as f:

pickle.dump(gestNames,f)

pickle.dump(knownGestures,f)

if train == 0:

if handData!=[]:

unknownGesture=findDistances(handData[0])

myGesture=findGesture(unknownGesture,knownGestures,keyPoints,gestNames,tol)

#error=findError(knownGesture,unknownGesture,keyPoints)

cv2.putText(frame,myGesture,(100,175),cv2.FONT_HERSHEY_SIMPLEX,3,(255,0,0),8)

for hand in handData:

for ind in keyPoints:

cv2.circle(frame,hand[ind],25,(255,0,255),3)

cv2.imshow('my WEBcam', frame)

cv2.moveWindow('my WEBcam',0,0)

if cv2.waitKey(1) & 0xff ==ord('q'):

break

cam.release()

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AI for Everyone LESSON 28: Storing and Loading Gesture Training Data in Mediapipe

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