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import streamlit as st | |
from transformers import pipeline | |
# Load the Hugging Face model | |
model_name = "linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification" | |
model = pipeline("image-classification", model=model_name) | |
# Streamlit app | |
st.title("Plant Disease Detection") | |
st.write("Upload an image of a plant leaf to detect the disease.") | |
# File uploader | |
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) | |
if uploaded_file is not None: | |
# Display the uploaded image | |
st.image(uploaded_file, caption="Uploaded Image", use_column_width=True) | |
st.write("Classifying...") | |
# Classify the image using the model | |
results = model(uploaded_file) | |
# Display the results | |
st.write("Results:") | |
for result in results: | |
st.write(f"{result['label']}: {result['score']:.2f}") | |
# Run the Streamlit app | |
if __name__ == "__main__": | |
st.run() | |