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import gradio as gr | |
from transformers import pipeline | |
# Load the image classification model | |
image_classification = pipeline("image-classification", model="ombhojane/healthyPlantsModel") | |
# Function to predict labels for the given image URL | |
def predict_labels(image_url): | |
result = image_classification(image_url) | |
return result[0] | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=predict_labels, | |
inputs=gr.Image(type="url", label="Input Image URL"), | |
outputs=gr.Textbox(label="Predicted Label"), | |
live=True | |
) | |
# Launch the Gradio interface | |
iface.launch() | |