import gradio as gr
from transformers import pipeline
from PIL import Image
import numpy as np
def predict_image(image):
pipe = pipeline("image-classification", model="itsTomLie/Jaundice_Classifier")
if isinstance(image, np.ndarray):
image = Image.fromarray(image.astype('uint8'))
elif isinstance(image, str):
image = Image.open(image)
result = pipe(image)
label = result[0]['label']
confidence = result[0]['score']
print(f"Prediction: {label}, Confidence: {confidence}")
return label, confidence
interface = gr.Interface(
fn=predict_image,
inputs=gr.Image(type="numpy", label="Upload an Image"),
outputs=[gr.Textbox(label="Prediction"), gr.Textbox(label="Confidence")]
)
interface.launch(debug=True)
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