Major-Project/predict.py at main · ashvtosh/Major-Project · GitHub

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import cv2
import numpy as np
from keras.models import model_from_json
import operator
import sys, os
import random
import string
from keras.models import load_model
from keras.models import model_from_json
with open("general1-bw.json","r") as file:
  general1_json=file.read()
  loaded_model=model_from_json(general1_json)
  loaded_model.load_weights("general1-bw.h5")
  print("Loaded model")
cam = cv2.VideoCapture(0)
categories = {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F',6:'G',7:'H',8:'I',9:'J',10:'K',11:'L',12:'M',13:'N',14:'O',15:'P',16:'Q',17:'R',18:'S',19:'T',20:'U',21:'V',22:'W',23:'X',24:'Y',25:'Z'}
while(cam.isOpened()):
    ret, frame = cam.read()
    frame=cv2.flip(frame,1)
    x1 = int(0.5*frame.shape[1])
    y1 = 10
    x2 = frame.shape[1]-10
    y2 = int(0.5*frame.shape[1])
    cv2.rectangle(frame, (x1-1, y1-1), (x2+1, y2+1), (255,0,0) ,2)
    roi = frame[y1:y2, x1:x2]
    minvalue=20
    roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
    _, roi = cv2.threshold(roi, 120, 255, cv2.THRESH_BINARY)
    roi=cv2.resize(roi,(128,128))
    cv2.imshow("sign detection",roi)
    result= loaded_model.predict(roi.reshape(1,128,128,1))
    prediction = {'A': result[0][0],
                  'B': result[0][1],
                  'C': result[0][2],
                  'D': result[0][3],
                  'E': result[0][4],
                  'F': result[0][5],
                  'G': result[0][6],
                  'H': result[0][7],
                  'I': result[0][8],
                  'J': result[0][9],
                  'K': result[0][10],
                  'L': result[0][11],
                  'M': result[0][12],
                  'N': result[0][13],
                  'O': result[0][14],
                  'P': result[0][15],
                  'Q': result[0][16],
                  'R': result[0][17],
                  'S': result[0][18],
                  'T': result[0][19],
                  'U': result[0][20],
                  'V': result[0][21],
                  'W': result[0][22],
                  'X': result[0][23],
                  'Y': result[0][24],
                  'Z': result[0][25],}
    prediction=sorted(prediction.items(),key=operator.itemgetter(1),reverse=True)
    frame = cv2.putText(frame, 'Predicted text: ', (50,70), cv2.FONT_HERSHEY_SIMPLEX,1, (0,255,0), 5, cv2.LINE_AA)
    cv2.putText(frame, prediction[0][0], (70, 200), cv2.FONT_HERSHEY_PLAIN, 10, (0,0,255), 10)
    cv2.imshow("FRAME",frame)

    interrupt=cv2.waitKey(10)
    if interrupt & 0xFF==27:
       break

cam.release()
cv2.destroyAllWindows()