Create app.py

app.py

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+import gradio as gr
+from paddleocr import PaddleOCR
+import cv2
+import numpy as np
+
+# Initialize OCR engine (loads models into memory once)
+# lang='en' supports English. Change to 'ch' for Chinese/English mix.
+ocr = PaddleOCR(use_angle_cls=True, lang='en', use_gpu=False)
+
+def run_ocr(image):
+    if image is None:
+        return "No image provided"
+
+    # Gradio passes image as numpy array, perfect for PaddleOCR
+    result = ocr.ocr(image, cls=True)
+
+    txts = []
+    if result and result[0]:
+        # Extract just the text from the complex result
+        txts = [line[1][0] for line in result[0]]
+
+    return "\n".join(txts)
+
+# Create the interface
+# The 'api_name' is crucial - it's how your HTML file will find this function
+demo = gr.Interface(
+    fn=run_ocr,
+    inputs=gr.Image(type="numpy"),
+    outputs="text",
+)
+
+if __name__ == "__main__":
+    demo.launch()