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potato-leaf-disease's Introduction

Potato-Leaf-Disease Predictor

Problem Statement:-

"Every year, farmers face substantial economic losses and crop wastage due to diseases that affect potato plants. Two of the most devastating diseases that afflict potato leaves are Early Blight and Late Blight. These diseases are responsible for significant reductions in potato yields and can lead to severe economic hardship for farmers"

Thus the images are classified into 3 classes :

  • Healthy leaves

image

  • Late Blight leaves

image

  • Early Blight leaves

image

Technology stack used:-

  • Tensorflow
  • Numpy
  • Keras
  • Matplotlib
  • Pathlib

Dataset :-

The dataset is being taken from "Kaggle".

The dataset contains 15 different directories:-

  • Potato___Early_blight

  • Potato___Late_blight

  • Potato___healthy

each containing images in .jpg format.

Workflow:-

image

Output:-

image

The model accuracy after training the image dataset is > 97%.

potato-leaf-disease's People

Contributors

sanils2002 avatar achyut132002 avatar yashojha07 avatar

Watchers

avatar

Forkers

yashojha07 achyut132002

potato-leaf-disease's Issues

Image version 2.0

import matplotlib.pyplot as plt

Create a figure to display images

plt.figure(figsize=(15, 15))

Loop through the first batch of images and labels from the dataset

for image, label in dataset.take(1):
for i in range(12):
# Create subplots in a 3x4 grid
plt.subplot(3, 4, i + 1)

    # Display the image as uint8 (integer) type
    plt.imshow(image[i].numpy().astype('uint8'))

    # Set the title of the subplot to the corresponding class name
    plt.title(class_name[label[i]])

    # Hide the axis values
    plt.axis("off")

Show the plot

plt.show()

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