Create app.py

app.py

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+from paddleocr import PaddleOCR, draw_ocr
+from matplotlib import pyplot as plt
+import cv2
+import os
+import gradio as gr
+from typing import List
+
+lst = [state.name for state in us.states.STATES_AND_TERRITORIES]
+sst_lst = []
+for i in lst:
+    sst_lst.append(i.upper())
+def ocr_model(filepath: str, languages: List[str]=None):
+    pocr_model = PaddleOCR(use_angle_cls=True, lang='ch', use_gpu=False)
+    # img_path = os.path.join('.', 'static', 'img10.jpg')
+    result = pocr_model.ocr(filepath)
+    state_txt = ""
+    for res in result :
+        state_txt += res[1][0] + "\n"
+    return state_txt
+
+title = "US Vehicle Number Plate"
+description = "Gradio demo for PaddlePaddle. PaddleOCR is an open source text recognition (OCR) Engine."
+article = "<p style='text-align: center'><a href='https://github.com/PaddlePaddle/PaddleOCR' target='_blank'>Github Repo</a></p>"
+
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(f'<h1 style="text-align: center; margin-bottom: 1rem;">{title}</h1>')
+    gr.Markdown(description)
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(type="filepath", label="Input")
+            with gr.Row():
+                btn_clear = gr.ClearButton([image])
+                btn_submit = gr.Button(value="Submit", variant="primary")
+        with gr.Column():
+            text = gr.Textbox(label="Output")
+
+    btn_submit.click(ocr_model, inputs=[image], outputs=text, api_name="PaddleOCR")
+    btn_clear.add(text)
+
+    gr.Markdown(article)
+
+if __name__ == '__main__':
+    demo.launch(share=True)