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arpan65 / Scanned-document-classification-deep-learning

BFSI sectors deal with lots of unstructured scanned documents which are archived in document management systems for further use.For example in Insurance sector, when a policy goes for underwriting, underwriters attached several raw notes with the policy, Insureds also attach various kind of scanned documents like identity card, bank statement, letters etc. In later parts of the policy life cycle if claims are made on a policy, releted scanned documents also archeived.Now it becomes a tedious job to identify a particular document from this vast repository. The goal of this case study is to develop a deep learning based solution which can automatically classify scanned documents.
MIT License
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Poor Performance for vgg16_85.h5 model #4

Open eddyjarjoura opened 4 years ago

eddyjarjoura commented 4 years ago

First of all, nice project. After using vgg16_85 model. I get a false result, I need to know where is my mistake.


model1 = load_model(r"/content/drive/My Drive/Models/vgg16_85.h5") 
img=cv2.imread("/content/drive/My Drive/s.png",cv2.COLOR_RGB2GRAY)
image = cv2.resize(img, (224, 224))
cv2_imshow(image)
image = img_to_array(image)
image = image/255
image = image.reshape((1, image.shape[0], image.shape[1], image.shape[2]))
#image = preprocess_input(image)
print("vgg16",classes[str(np.argmax(model1.predict(image)))])