Initial upload for the app

app.py

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+import gradio as gr
+import PIL
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+from translate import Translator
+
+def translate_text(text, src_lang='en', dest_lang='vi'):
+    translator = Translator(to_lang=dest_lang, from_lang=src_lang)
+    translation = translator.translate(text)
+    return translation
+
+def process_image(input_image):
+    # Convert the uploaded image data to a PIL Image
+    image = Image.open(input_image.name).convert('RGB')
+    
+    # Sample code to perform OCR and draw translated text (replace with your logic)
+    # Simulated results for demonstration purposes
+    result = [
+        ([(100, 100), (200, 100), (200, 200), (100, 200)], ("Hello, how are you?", 0.95))
+    ]
+
+    draw = PIL.ImageDraw.Draw(image)
+    for i, box in enumerate(result):
+        text = translate_text(box[1][0])
+        box = np.array(box[0]).astype(np.int32)
+        xmin = min(box[:, 0])
+        ymin = min(box[:, 1])
+        xmax = max(box[:, 0])
+        ymax = max(box[:, 1])
+        draw.rectangle((xmin, ymin, xmax, ymax), outline="red", width=1)
+        draw.text((xmin + 40, ymin + 40), f"{text}", fill="black", font=ImageFont.load_default())
+
+    # Save the processed image
+    processed_image_path = 'processed_image.jpg'
+    image.save(processed_image_path)
+    return processed_image_path
+
+iface = gr.Interface(
+    fn=process_image, 
+    inputs=gr.inputs.Image(type="pil", label="Upload Image"),
+    outputs="image",
+    title="OCR Translation App",
+    description="Upload an image and see the processed image with translated text."
+)
+iface.launch()

requirements.txt

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+paddlepaddle
+Pillow
+translate
+gradio
+paddleocr>=2.0.1