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import gradio as gr
from paddleocr import PaddleOCR
from PIL import Image, ImageOps
import numpy as np
# Initialize PaddleOCR
ocr = PaddleOCR(use_angle_cls=True, lang='en')
# Function to process captured images
def process_image(image, camera_type="rear"):
if image is None:
return "No image captured."
# Flip the image horizontally for the rear camera
if camera_type == "rear":
image = ImageOps.mirror(image)
# Perform OCR on the corrected image
result = ocr.ocr(np.array(image))
extracted_text = []
for line in result[0]:
extracted_text.append(line[1][0])
return "\n".join(extracted_text)
# Gradio Interface
def create_app():
with gr.Blocks() as app:
gr.Markdown("## OCR Processor with Rear Camera Fix")
# Inputs for image capture and camera type selection
with gr.Row():
image_input = gr.Image(type="pil", label="Capture Image") # For image capture
camera_type = gr.Dropdown(
choices=["rear", "front"],
value="rear",
label="Camera Type"
)
# Output for extracted text
extracted_text = gr.Textbox(label="Extracted Text")
# Button to process the captured image
process_button = gr.Button("Process Image")
process_button.click(
fn=process_image,
inputs=[image_input, camera_type],
outputs=extracted_text
)
return app
if __name__ == "__main__":
create_app().launch(share=True)
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