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gridOfImage.py
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gridOfImage.py
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import os
import sys
import cv2
from keras.models import load_model
import numpy as np
from PIL import Image
from itertools import product
model = load_model('imp.h5')
def image(path):
img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
new_arr = cv2.resize(img, (120, 120))
new_arr = np.array(new_arr)
new_arr = new_arr.reshape(-1, 120, 120, 1)
return new_arr
img= str(sys.args[1])
noofimage = int(sys.args[2])
for i in range(1,noofimage):
k = i*i
if(k == noofimage):
count = i
break
CATEGORIES = ['Speed limit (20km/h)','Speed limit (30km/h)','Speed limit (50km/h)','Speed limit (60km/h)','Speed limit (70km/h)',
'Speed limit (80km/h)','End of speed limit (80km/h)','Speed limit (100km/h)','Speed limit (120km/h)','No passing',
'No passing veh over 3.5 tons','Right-of-way at intersection','Priority road','Yield','Stop','No vehicles',
'Veh > 3.5 tons prohibited','No entry','General caution','Dangerous curve left','Dangerous curve right','Double curve',
'Bumpy road','Slippery road','Road narrows on the right','Road work','Traffic signals','Pedestrians',
'Children crossing','Bicycles crossing','Beware of ice/snow','Wild animals crossing','End speed + passing limits',
'Turn right ahead','Turn left ahead','Ahead only','Go straight or right','Go straight or left','Keep right',
'Keep left','Roundabout mandatory','End of no passing','End no passing veh > 3.5 tons','Car','Buildings',
'Forest', 'Glacier','Mountain','Sea','Street','Vehicle']
name,ext = os.path.splitext(img)
img = Image.open(img)
w, h = img.size
hd = h//count
wd = w//count
m=1
path = 'Temp/'
splitimagename = []
grid = product(range(0,h-h%hd,hd), range(0,w-w%wd,wd))
for i, j in grid:
box = (j,i,j+wd, i+hd)
out = path+ str(m) + ext
splitimagename.append(out)
m+=1
img.crop(box).save(out)
for i in splitimagename:
im = cv2.imread(i)
prediction = model.predict([image(i)])
print(CATEGORIES[prediction.argmax()])
for img in os.listdir(path):
file = path+img
os.remove(file)