app.py

import gradio as gr
from predict import ONNXInference
import json

def detect(files):
    model = ONNXInference(
        model_path="./torchFlow-ckpt.onnx",
        files=files,
        save_image=False,
        save_path="./"
    )
    res = model.run()
    # img_id = res["IMG_ID"]
    # pred_lab = res["PRED_LAB"],
    # pred_ct = res["PRED_CT"],
    # geo_tag_url =  res["GEO_TAG_URL"]

    result = json.dumps(res)
    return result

with gr.Blocks() as demo:
    gr.Markdown("# DetectIt")
    with gr.Row():
        image = gr.UploadButton(
            label="Upload Image",
            file_types=[".jpg",".jpeg"],
            file_count="multiple")

        btn = gr.Button("Go")
    text = gr.Textbox(show_label=False, elem_id="result-textarea")
    btn.click(detect, inputs=[image], outputs=[text], api_name="predict")

demo.launch()