def solveEqsFromWebcam(withRespectTo):
symbols = [
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '=', 'x', '+', '-',
'y'
]
json_file = open('models/model_balanced.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
loaded_model.load_weights("models/model_balanced.h5")
classifier = ClassifierKeras(symbols, loaded_model)
cv2.namedWindow("preview", cv2.WINDOW_NORMAL)
vc = cv2.VideoCapture(0)
if vc.isOpened():
rval, frame = vc.read()
else:
rval = False
while rval:
cv2.resizeWindow("preview", 640, 480)
rval, frame = vc.read()
key = cv2.waitKey(20)
if key == 27: # ESC
break
# treat frame
cv2.imwrite("screencap.jpg", frame)
img = ip.getImgMat("screencap.jpg")
chars = ip.extractCharacters(img, (45, 45))
for char in chars:
classifier.classify(char)
lines = parseEquation(chars)
drawSolvedEquations(lines, frame, withRespectTo)
cv2.imshow("preview", frame)
cv2.destroyWindow("preview")
def solveEqFromImage(withRespectTo):
img = ip.getImgMat('images/twoEq.jpg')
chars = ip.extractCharacters(img, (45, 45))
lines = parseEquation(chars)
symbols = [
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '=', 'x', '+', '-',
'y'
]
json_file = open('models/model_balanced.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
loaded_model.load_weights("models/model_balanced.h5")
classifier = ClassifierKeras(symbols, loaded_model)
print("Equations:\n")
for line in lines:
for group in line:
str = ""
for c in group:
classifier.classify(c)
str += c.symbol
print(str, end="\t")
print("")
print("\nSolutions:\n")
eqs = toSymPyFormat(lines)
for eq in eqs:
solveSingleEq(eq, withRespectTo)
img = cv2.pyrDown(img)
cv2.imshow("test", img)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()
def classifyCharsFromWebcam():
symbols = [
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '=', 'x', '+', '-',
'y'
]
json_file = open('models/model_balanced.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
loaded_model.load_weights("models/model_balanced.h5")
classifier = ClassifierKeras(symbols, loaded_model)
cv2.namedWindow("preview", cv2.WINDOW_NORMAL)
vc = cv2.VideoCapture(0)
if vc.isOpened():
rval, frame = vc.read()
else:
rval = False
while rval:
cv2.resizeWindow("preview", 640, 480)
rval, frame = vc.read()
key = cv2.waitKey(20)
if key == 27: # ESC
break
#Process frame
cv2.imwrite("screencap.jpg", frame)
threshed_img = ip.getImgMat("screencap.jpg")
characters = ip.extractCharacters(threshed_img, (45, 45))
imgWithBounds = ip.drawCharacterBounds(frame, characters)
classifiedImg = ip.drawClassifiedCharacters(imgWithBounds, classifier,
characters)
cv2.imshow("preview", classifiedImg)
cv2.destroyWindow("preview")
def classifyCharsFromImage():
symbols = [
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '=', 'x', '+', '-',
'y'
]
json_file = open('models/model_balanced.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
loaded_model.load_weights("models/model_balanced.h5")
classifier = ClassifierKeras(symbols, loaded_model)
imgPath = 'images/twoEq.jpg'
img = ip.getImgMat(imgPath)
chars = ip.extractCharacters(img)
imgRect = img.copy()
ip.drawCharacterBounds(imgRect, chars)
ip.drawClassifiedCharacters(imgRect, classifier, chars)
cv2.imshow("Classifications", imgRect)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()
import Network as nw
import imageProcessor as ip
import Classifier as cl
import numpy as np
import cv2
import mnist_loader
imgMat = ip.getImgMat('ex.png')
chars = ip.extractCharacters(imgMat, (28, 28))
#net = nw.Network([784,100,10])
trainingData, validationData, testData = mnist_loader.load_data_wrapper()
#net.train(trainingData, 3 ,10, 3.0, testData = testData)
net = nw.load('mnist.json')
a = testData[0]
print(a)
#print(imgMat)
clas = cl.Classifier(['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'], net)
for c in chars:
clas.classify(c)
print(c.symbol)
cv2.putText(imgMat, c.symbol, (c.xPos, c.yPos), cv2.FONT_HERSHEY_SIMPLEX,
2, 0)
cv2.imshow("test", imgMat)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()