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import gradio as gr
from predict import ONNXInference
PRED = []
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"]
PRED.append(pred_ct)
return f"Predicted: {PRED}"
with gr.Blocks() as demo:
with gr.Row():
output=gr.File()
with gr.Row():
# text = gr.Textbox(show_label=False, elem_id="result-textarea")
btn = gr.UploadButton(
label="Upload Image",
file_types=[".jpg",".jpeg"],
file_count="multiple")
btn.upload(fn=detect, inputs=btn, outputs=[gr.Textbox(show_label=False, elem_id="result-textarea")], api_name="predict")
# put gr.Label() in upload(outputs=gr.Label())
demo.launch() |