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Update app.py
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app.py
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import gradio as gr
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from paddleocr import PaddleOCR
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from PIL import Image
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import numpy as np
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# Initialize PaddleOCR
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ocr = PaddleOCR(use_angle_cls=True, lang='en')
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# Function to process uploaded
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def process_uploaded_image(image):
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if image is None:
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return "No image uploaded."
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#
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result = ocr.ocr(np.array(image))
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extracted_text = []
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for line in result[0]:
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return "\n".join(extracted_text)
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# Gradio Interface
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if __name__ == "__main__":
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import gradio as gr
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from paddleocr import PaddleOCR
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from PIL import Image, ImageOps
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import numpy as np
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# Initialize PaddleOCR
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ocr = PaddleOCR(use_angle_cls=True, lang='en')
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# Function to process uploaded/captured images
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def process_uploaded_image(image, camera_type="rear"):
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if image is None:
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return "No image uploaded."
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# Mirror the image for rear camera
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if camera_type == "rear":
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image = ImageOps.mirror(image)
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# Perform OCR on the corrected image
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result = ocr.ocr(np.array(image))
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extracted_text = []
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for line in result[0]:
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return "\n".join(extracted_text)
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# Gradio Interface
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def create_app():
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with gr.Blocks() as app:
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gr.Markdown("## OCR Processor with Rear Camera Fix")
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# Input for image capture and camera type selection
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with gr.Row():
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image_input = gr.Image(source="webcam", type="pil", label="Capture Image from Webcam")
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camera_type = gr.Dropdown(
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choices=["rear", "front"],
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value="rear",
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label="Camera Type"
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)
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# Output for extracted text
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extracted_text = gr.Textbox(label="Extracted Text")
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# Button to process the image
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process_button = gr.Button("Process Image")
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process_button.click(
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fn=process_uploaded_image,
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inputs=[image_input, camera_type],
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outputs=extracted_text
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)
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return app
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if __name__ == "__main__":
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create_app().launch(share=True)
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