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We need to include models and processing packages that are specific to that model.
Import image
from tensorflow.keras.preprocessing
.
from << your code comes here >> import << your code comes here >>
Import ResNet50
as myModel
from tensorflow.keras.applications.resnet50
.
from tensorflow.keras.applications.resnet50 import << your code comes here >> as << your code comes here >>
Import preprocess_input
, decode_predictions
from tensorflow.keras.applications.resnet50
.
from tensorflow.keras.applications.resnet50 import << your code comes here >>
Now get the model model
and include the weights of "imagenet"
data classification task. We will be using this trained network to predict the class of our desired image.
model = myModel(weights="imagenet")
Note- If you face Unable to open file
error while loading the model, refer to Input/Output Error(Error no. 5).
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