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from keras.models import load_model | |
from keras.preprocessing import image | |
import numpy as np | |
import os | |
# image folder | |
folder_path = '/path/to/folder/' | |
# path to model | |
model_path = '/path/to/saved/model.h5' | |
# dimensions of images | |
img_width, img_height = 320, 240 | |
# load the trained model | |
model = load_model(model_path) | |
model.compile(loss='binary_crossentropy', | |
optimizer='rmsprop', | |
metrics=['accuracy']) | |
# load all images into a list | |
images = [] | |
for img in os.listdir(folder_path): | |
img = os.path.join(folder_path, img) | |
img = image.load_img(img, target_size=(img_width, img_height)) | |
img = image.img_to_array(img) | |
img = np.expand_dims(img, axis=0) | |
images.append(img) | |
# stack up images list to pass for prediction | |
images = np.vstack(images) | |
classes = model.predict_classes(images, batch_size=10) | |
print(classes) |
Hello,
I have a similar problem like @BhagyasriYella, only that my classifier uses rescaled images. I solved this in the code via
img /= 255.
classes = model.predict_classes(img, batch_size=10)
img *= 255.
However, with the rescaling and without, I do get my original images (.jpg) classified correctly (as seen on the names) but somehow I cannot open them and they are 0KB. Any ideas on why that is?
Hello,
can you please help me with my issue:
I want to show the results on a table showing the correct and incorrect predictions but after several tries I have not been able to implement the prettytable correctly in your code.
Can you please help me!
Thank you in advance
Hello
can you please help me !
if I want to save the predicted images into a folder ,how should I do it!
It worked Thanks..
Thank you for the code! I just had to substitute img_to_array(img) to np.asarray(img), then it worked.
I am getting following error while running above code
AttributeError: 'Model' object has no attribute 'predict_classes'
Hello, please help. I am getting this error:
cannot identify image file <_io.BytesIO object at 0x7fbe54eb8090>
Did you get any reply regarding it?