I am trying to run the following code : The code loads an existing model "model_6cat.h5" and runs a prediction using same.
我正在尝试运行以下代码:代码加载一个现有模型“model_6cat”。并使用同样的方法运行一个预测。
from keras.models import load_model
import matplotlib.pyplot as plt
import numpy as np
import copy
import cv2
import os
dataColor = (0,255,0)
font = cv2.FONT_HERSHEY_SIMPLEX
fx, fy, fh = 10, 50, 45
takingData = 0
className = 'NONE'
count = 0
showMask = 0
classes = 'NONE ONE TWO THREE FOUR FIVE'.split()
def initClass(name):
global className, count
className = name
os.system('mkdir -p data/%s' % name)
count = len(os.listdir('data/%s' % name))
def binaryMask(img):
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img = cv2.GaussianBlur(img, (7,7), 3)
img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
ret, new = cv2.threshold(img, 25, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
return new
def main():
global font, size, fx, fy, fh
global takingData, dataColor
global className, count
global showMask
model = load_model('model_6cat.h5')
x0, y0, width = 200, 220, 300
cam = cv2.VideoCapture(0)
cv2.namedWindow('Original', cv2.WINDOW_NORMAL)
while True:
# Get camera frame
ret, frame = cam.read()
frame = cv2.flip(frame, 1) # mirror
window = copy.deepcopy(frame)
cv2.rectangle(window, (x0,y0), (x0+width-1,y0+width-1), dataColor, 12)
# draw text
if takingData:
dataColor = (0,250,0)
cv2.putText(window, 'Data Taking: ON', (fx,fy), font, 1.2, dataColor, 2, 1)
else:
dataColor = (0,0,250)
cv2.putText(window, 'Data Taking: OFF', (fx,fy), font, 1.2, dataColor, 2, 1)
cv2.putText(window, 'Class Name: %s (%d)' % (className, count), (fx,fy+fh), font, 1.0, (245,210,65), 2, 1)
# get region of interest
roi = frame[y0:y0+width,x0:x0+width]
roi = binaryMask(roi)
# apply processed roi in frame
if showMask:
window[y0:y0+width,x0:x0+width] = cv2.cvtColor(roi, cv2.COLOR_GRAY2BGR)
# take data or apply predictions on ROI
if takingData:
cv2.imwrite('data/{0}/{0}_{1}.png'.format(className, count), roi)
count += 1
else:
img = np.float32(roi)/255.
img = np.expand_dims(img, axis=0)
img = np.expand_dims(img, axis=-1)
pred = classes[np.argmax(model.predict(img)[0])]
cv2.putText(window, 'Prediction: %s' % (pred), (fx,fy+2*fh), font, 1.0, (245,210,65), 2, 1)
# use below for demoing purposes
#cv2.putText(window, 'Prediction: %s' % (pred), (x0,y0-25), font, 1.0, (255,0,0), 2, 1)
# show the window
cv2.imshow('Original', window)
# Keyboard inputs
key = cv2.waitKey(10) & 0xff
# use q key to close the program
if key == ord('q'):
break
# Toggle data taking
elif key == ord('s'):
takingData = not takingData
elif key == ord('b'):
showMask = not showMask
# Toggle class
elif key == ord('0'): initClass('NONE')
elif key == ord('`'): initClass('NONE') # because 0 is on other side of keyboard
elif key == ord('1'): initClass('ONE')
elif key == ord('2'): initClass('TWO')
elif key == ord('3'): initClass('THREE')
elif key == ord('4'): initClass('FOUR')
elif key == ord('5'): initClass('FIVE')
# adjust the size of window
#elif key == ord('z'):
# width = width - 5
#elif key == ord('a'):
# width = width + 5
# adjust the position of window
elif key == ord('i'):
y0 = max((y0 - 5, 0))
elif key == ord('k'):
y0 = min((y0 + 5, window.shape[0]-width))
elif key == ord('j'):
x0 = max((x0 - 5, 0))
elif key == ord('l'):
x0 = min((x0 + 5, window.shape[1]-width))
cam.release()
if __name__ == '__main__':
initClass('NONE')
main()
and because the network wanted to have input_shape as 300x300 but my model is 260x300, i am getting the error message "ValueError: Error when checking : expected conv2d_1_input to have shape (None, 300, 300, 1) but got array with shape (1, 260, 300, 1)" during the runtime.
由于网络希望input_shape为300x300，但我的模型是260x300，所以我在运行时得到了错误消息“ValueError: check时出错:expected conv2d_1_input为shape (None, 300,300, 1)，而array为shape(1,260, 300, 1)”。
Traceback (most recent call last):
File "application.py", line 137, in <module>
main()
File "application.py", line 84, in main
pred = classes[np.argmax(model.predict(img)[0])]
File "/home/pankaj/vev/lib/python3.5/site-packages/keras/models.py", line 913, in predict
return self.model.predict(x, batch_size=batch_size, verbose=verbose)
File "/home/pankaj/vev/lib/python3.5/site-packages/keras/engine/training.py", line 1695, in predict
check_batch_axis=False)
File "/home/pankaj/vev/lib/python3.5/site-packages/keras/engine/training.py", line 144, in _standardize_input_data
str(array.shape))
ValueError: Error when checking : expected conv2d_1_input to have shape (None, 300, 300, 1) but got array with shape (1, 260, 300, 1)
is there any quickfix for this issue? or do i have to re-create the model?
对于这个问题有什么快速解决方法吗?还是需要重新创建模型?
2 个解决方案
#1
1
Your model expects images 300x300 and you're giving it an image 260x300.
你的模型期望图像300x300，你给它一个图像260x300。
#2
0
Change Your code:-
改变你的代码:-
x0, y0, width = 200, 220, 300
to
来
x0, y0, width = 200, 180, 300
and see the result.
并看到结果。
#1
1
Your model expects images 300x300 and you're giving it an image 260x300.
你的模型期望图像300x300，你给它一个图像260x300。
#2
0
Change Your code:-
改变你的代码:-
x0, y0, width = 200, 220, 300
to
来
x0, y0, width = 200, 180, 300
and see the result.
并看到结果。