import gradio as gr from huggingface_hub import InferenceAPI # Specify the model name model_repo = "jdelgado2002/diabetic_retinopathy_detection" # Initialize the InferenceAPI client api = InferenceAPI(model_repo) labels = ["No DR", "Mild", "Moderate", "Severe", "Proliferative DR"] def predict(img): # Convert the image to a base64 string img_str = gr.inputs.Image.to_base64(img, ext="jpeg") # Perform inference inputs = {"inputs": img_str} result = api(inputs) # Convert the result to the expected format return {labels[i]: float(result[i]) for i in range(len(labels))} title = "Proliferative Retinopathy Detection" description = """Detects severity of diabetic retinopathy - 0 - No DR 1 - Mild 2 - Moderate 3 - Severe 4 - Proliferative DR """ article="
" interpretation='default' enable_queue=True gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=6),title=title,description=description,article=article,interpretation=interpretation,enable_queue=enable_queue).launch()