import gradio as gr
# Import tensorflow here
import tensorflow as tf
from tensorflow.keras.utils import img_to_array,load_img
from tensorflow.keras.models import load_model # Use tensorflow.keras.models
import numpy as np
# Load the pre-trained model from the local path
model_path = 'Mango.h5'
# Define custom objects to handle potential incompatibilities
custom_objects = {'DepthwiseConv2D': tf.keras.layers.DepthwiseConv2D}
# Load the model with custom_objects
model = load_model(model_path, custom_objects=custom_objects) # Load the model here
def predict_disease(image_file, model, all_labels):
try:
# Load and preprocess the image
img = load_img(image_file, target_size=(224, 224)) # Use load_img from tensorflow.keras.utils
img_array = img_to_array(img)
img_array = np.expand_dims(img_array, axis=0) # Add batch dimension
img_array = img_array / 255.0 # Normalize the image
# Predict the class
predictions = model.predict(img_array) # Use the loaded model here
predicted_class = np.argmax(predictions[0])
# Get the predicted class label
predicted_label = all_labels[predicted_class]
# Print the predicted label to the console
if predicted_label=='Mango Anthracrose':
predicted_label = """
Mango Anthracrose
PESTICIDES TO BE USED:
- 1. Mancozeb
- 2. Azoxystrobin
- 3. carbendazim
- 4. Propiconazole
- 5. Thiophanate-methyl
- 6. Copper Sulfate
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Bacterial Canker':
predicted_label = """
Mango Bacterial Canker
PESTICIDES TO BE USED:
- 1. Copper Hydroxide
- 2. Copper Oxychloride
- 3. Streptomycin
- 4. oxytetracycline
- 5. Neem oil
- 6. Garlic oil
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Cutting Weevil':
predicted_label = """
Mango Cutting Weevil
PESTICIDES TO BE USED:
- 1. Imidacloprid
- 2. Thiamethoxam
- 3. Chlorpyrifos
- 4. Lambda-cyhalothrin
- 5. Fipronil
- 6. Neem oil
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Die Back':
predicted_label = """
Mango Die Back
PESTICIDES TO BE USED:
- 1. Carbendazim
- 2. Mancozeb
- 3. Azoxystrobin
- 4. Triazole
- 5. Potassium bicarbonate
- 6. Sodium bicarbonate
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Gall Midge':
predicted_label = """
Mango Gall Midge
PESTICIDES TO BE USED:
- 1. Imidacloprid
- 2. Thiamethoxam
- 3. Chlorpyrifos
- 4. Lambda-cyhalothrin
- 5. Spinosad
- 6. Pyrethrin
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Powdery Mildew':
predicted_label = """
Mango Powdery Mildew
PESTICIDES TO BE USED:
- 1. Sulfur
- 2. Bicarbonates
- 3. Myclobutanil
- 4. Triadimefon
- 5. Propiconazole
- 6. Azoxystrobin
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
elif predicted_label=='Mango Sooty Mould':
predicted_label = """
Mango Sooty Mould
PESTICIDES TO BE USED:
- 1. Imidacloprid (Neonicotinoid)
- 2. Thiamethoxam (Neonicotinoid)
- 3. Bifenthrin (Pyrethroid)
- 4. Lambda-cyhalothrin (Pyrethroid)
- 5. Insecticidal soap
- 6. Horticultural oil
* * * IMPORTANT NOTE * * *
Be sure to follow local regulations and guidelines for application
"""
else:
predicted_label = """Mango Healthy
No need use Pesticides"""
return predicted_label
except Exception as e:
print(f"Error: {e}")
return None
# List of class labels
all_labels = [
'Mango Anthracrose',
'Mango Bacterial Canker',
'Mango Cutting Weevil',
'Mango Die Back',
'Mango Gall Midge',
'Mango Healthy',
'Mango Powdery Mildew',
'Mango Sooty Mould'
]
# Define the Gradio interface
def gradio_predict(image_file):
return predict_disease(image_file, model, all_labels) # Pass the model to the function
# Create a Gradio interface
gr_interface = gr.Interface(
fn=gradio_predict, # Function to call for predictions
inputs=gr.Image(type="filepath"), # Upload image as file path
outputs="html", # Output will be the class label as text
title="Mango Disease Predictor",
description="Upload an image of a plant to predict the disease.",
)
# Launch the Gradio app
gr_interface.launch(share=True)