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()