In this lab, you will design a CNN that can detect diseased or healthy plant leaves. 

**#Computer Vision****
"Computer vision is an area of machine learning dedicated to interpreting and understanding images and video. It is used to help teach computers to “see” and to use visual information to perform visual tasks that humans can." (https://www.run.ai/guides/deep-learning-for-computer-vision#:~:text=Computer%20vision%20algorithms%20analyze%20certain,commonly%20used%20for%20computer%20vision.) 

The link above is a great source to learn more about computer vision and how the CNN behind it work.

# **Code Example of CNN Model**
\```model = models.Sequential()
model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(300, 150, 3)))
model.add(layers.MaxPooling2D((2, 2)))
model.add(layers.Conv2D(64, (3, 3), activation='relu'))\```

# **Instructions**
1. Load and look through the data
2. I suggest some potential image augmentation, this is a large dataset
3. Design a CNN that is able to accurately detect diseased and healthy leaves (Example above)
- Try and find parameters that will give the best accuracy 
4. Look at sample submission on what you submission should look like