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import os |
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import gradio as gr |
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from Plan.AiLLM import llm_recognition |
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from Plan.pytesseractOCR import ocr_recognition |
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from Preprocess.preprocessImg import preprocess_image001, preprocess_image002 |
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languages = os.popen('tesseract --list-langs').read().split('\n')[1:-1] |
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def preprocess_and_ocr(image, valid_type, language): |
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pre_img_001 = preprocess_image001(image) |
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ocr_result_001 = ocr_recognition(pre_img_001, valid_type, language) |
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pre_img_002 = preprocess_image002(image) |
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ocr_result_002 = ocr_recognition(pre_img_002, valid_type, language) |
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return pre_img_001, pre_img_002, ocr_result_001, ocr_result_002 |
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def preprocess_and_llm(image, valid_type, language): |
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pre_img_001 = preprocess_image001(image) |
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llm_result_001 = llm_recognition(pre_img_001, valid_type, language) |
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pre_img_002 = preprocess_image002(image) |
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llm_result_002 = llm_recognition(pre_img_002, valid_type, language) |
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return pre_img_001, pre_img_002, llm_result_001, llm_result_002 |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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image_input = gr.Image(type="pil", label="上傳圖片") |
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preprocess_output_001 = gr.Image(type="pil", label="預處理後的圖片-方案一") |
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preprocess_output_002 = gr.Image(type="pil", label="預處理後的圖片-方案二") |
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with gr.Row(): |
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validation_type = gr.Dropdown(choices=["身分證正面", "身分證反面"], label="驗證類別") |
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language_dropdown = gr.Dropdown(choices=languages, value="chi_tra", label="語言") |
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with gr.Row(): |
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ocr_button = gr.Button("使用 OCR") |
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llm_button = gr.Button("使用 AI LLM") |
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with gr.Row(): |
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ocr_output_001 = gr.JSON(label="OCR-001-解析結果") |
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ocr_output_002 = gr.JSON(label="OCR-002-解析結果") |
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llm_output_001 = gr.JSON(label="AiLLM-001 解析結果") |
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llm_output_002 = gr.JSON(label="AiLLM-002 解析結果") |
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ocr_button.click(preprocess_and_ocr, inputs=[image_input, validation_type, language_dropdown], |
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outputs=[preprocess_output_001, preprocess_output_002, ocr_output_001, ocr_output_002]) |
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llm_button.click(preprocess_and_llm, inputs=[image_input, validation_type, language_dropdown], |
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outputs=[preprocess_output_001, preprocess_output_002, llm_output_001, llm_output_002]) |
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demo.launch(share=False) |
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