Image Classification
Keras
English
art
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@@ -54,9 +54,10 @@ Train the Model: Use the provided code to train the model on your dataset.
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  Evaluate: Test the model on a separate set of images to assess performance.
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  ## Training Details
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  ### Training Data
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  -Dataset: DataScienceProject/Art_Images_Ai_And_Real_
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  ### Training Procedure
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- Images are resized to a uniform dimension and normalized. ELA is applied to emphasize artifacts in the images.
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  #### Training Hyperparameters
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  ## Evaluation
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  ### Testing Data, Factors & Metrics
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  #### Testing Data
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  ### Results
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  Evaluate: Test the model on a separate set of images to assess performance.
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  ## Training Details
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  ### Training Data
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  -Dataset: DataScienceProject/Art_Images_Ai_And_Real_
 
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  ### Training Procedure
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+ Train the CNN with the Preprocessed images , use valitadion set.
 
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  #### Training Hyperparameters
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+ optimizer = RMSprop(lr=0.0005, rho=0.9, epsilon=1e-08, decay=0.0)
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+ epochs = 22
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+ batch_size = 100
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+ loss = "categorical_crossentropy"
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+ metrics=["accuracy"]
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+ early_stopping = EarlyStopping(monitor='val_acc',min_delta=0,patience=2,verbose=0, mode='auto')
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  ## Evaluation
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  ### Testing Data, Factors & Metrics
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+ precision
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+ recall
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+ f1
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+ confusion_matrix
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+ accuracy
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  #### Testing Data
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  ### Results
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