Adonai Vera
Model in private repo
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from turtle import title
import gradio as gr
from transformers import pipeline
from PIL import Image
# Initialize the pipeline with your model
pipe = pipeline("image-classification", model="SubterraAI/ofwat_material_classification")
def classify_image(image):
# Convert the input image to PIL format
PIL_image = Image.fromarray(image).convert('RGB')
# Classify the image using the pipeline
res = pipe(PIL_image)
# Extract labels and scores
return {dic["label"]: dic["score"] for dic in res}
# Create the Gradio interface
iface = gr.Interface(
classify_image,
"image",
"label",
examples=[
["examples/CS.jpg"],
["examples/GI.jpg"],
["examples/PP.jpg"],
["examples/RC.jpg"]
],
description="Upload an image to classify its material.",
title="Material Classification with AI by Subterra"
)
# Launch the interface
iface.launch()