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