MahaPala

Detection of fruits disease by using Machine learning

Indentification Of Fruits

Create class to indentify the fruit names tested it for Guava & Mango fruits

• Deep learning algorithm
• adam optimizer
• relu activation

Reference

• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4245116/

Model: sequential

_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 rescaling (Rescaling)       (None, 224, 224, 3)       0         
                                                                 
 conv2d (Conv2D)             (None, 224, 224, 16)      448       
                                                                 
 max_pooling2d (MaxPooling2  (None, 112, 112, 16)      0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 112, 112, 32)      4640      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 56, 56, 32)        0         
 g2D)                                                            
                                                                 
 conv2d_2 (Conv2D)           (None, 56, 56, 64)        18496     
                                                                 
 max_pooling2d_2 (MaxPoolin  (None, 28, 28, 64)        0         
 g2D)                                                            
                                                                 
 flatten (Flatten)           (None, 50176)             0         
                                                                 
 dense (Dense)               (None, 128)               6422656   
                                                                 
 dense_1 (Dense)             (None, 5)                 645       
                                                                 
=================================================================
Total params: 6446885 (24.59 MB)
Trainable params: 6446885 (24.59 MB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________

Dashboard

Release Note

2023.12.16

• #9 Create a sample to identify the fruits name
• #11 Implement visualization dashboard

2021.11.01

• #9 Create a sample to identify the fruits name

2020.11.01.dev

• Initial setup and environments
• Added a templete matching algorithm