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import gradio as gr |
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from predict import ONNXInference |
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import json |
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def detect(files): |
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model = ONNXInference( |
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model_path="./torchFlow-ckpt.onnx", |
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files=files, |
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save_image=False, |
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save_path="./" |
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) |
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res = model.run() |
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result = json.dumps(res) |
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return result |
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with gr.Blocks() as demo: |
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gr.Markdown("# DetectIt") |
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with gr.Row(): |
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image = gr.UploadButton( |
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label="Upload Image", |
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file_types=[".jpg",".jpeg"], |
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file_count="multiple") |
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btn = gr.Button("Go") |
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text = gr.Textbox(show_label=False, elem_id="result-textarea") |
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btn.click(detect, inputs=[image], outputs=[text], api_name="predict") |
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demo.launch() |