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plant_diseases_classification_model

For this particular project, I used TensorFlow==2.6.4, EfficientNetB0 pre-trained model for Transfer_learning freezing the base_model. Regarding Fine-tune_model, I used a separate code block to explain the process. The model predicts label_name by providing image_path from test_set.

What is EfficientNet?

It was introduced by GoogleAI in 2019. It is a CNN architecture and scaling method that uniformly scales all dimensions of CNN such as depth, width, and resolution using a compound co-efficient.

It provides a way to scale up CNNs in a more structured manner while also balancing all dimensions of the network at once, leading to a significant improvement in both accuracy and efficiency.

EfficientNet has 8 models from b0 to b7. Each model has 4 components given below-

  1. Stem layer
  2. Final Layer
  3. Sub-blocks (Each block has sub-blocks.)
  4. Modules (Each sub-blocks has modules.)

Layer details:

Input Layer -> Rescaling -> Normalization -> Zero Padding -> Conv2D -> Batch Normalization -> Activation

Models' details:

Base Model Resolution (Input shapes)
EfficientNetB0 224
EfficientNetB1 240
EfficientNetB2 260
EfficientNetB3 300
EfficientNetB4 380
EfficientNetB5 456
EfficientNetB6 528
EfficientNetB7 600

Reference:

  1. Dataset link: https://lnkd.in/eVyxTqrX