Create app.py

app.py

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+import pandas as pd
+from PIL import Image, ImageDraw
+import gradio as gr
+import torch
+import easyocr
+
+# 📥 Let's download some sample images to play with!
+def download_sample_images():
+    image_urls = {
+        '20-Books.jpg': 'https://raw.githubusercontent.com/AaronCWacker/Yggdrasil/master/images/20-Books.jpg',
+        'COVID.png': 'https://github.com/JaidedAI/EasyOCR/raw/master/examples/english.png',
+        'chinese.jpg': 'https://github.com/JaidedAI/EasyOCR/raw/master/examples/chinese.jpg',
+        'japanese.jpg': 'https://github.com/JaidedAI/EasyOCR/raw/master/examples/japanese.jpg',
+        'Hindi.jpeg': 'https://i.imgur.com/mwQFd7G.jpeg'
+    }
+    for filename, url in image_urls.items():
+        # 🛸 Beaming down image: {filename}
+        torch.hub.download_url_to_file(url, filename)
+
+# 🖌️ Function to draw boxes around detected text (because we all love boxes)
+def draw_boxes(image, bounds, color='yellow', width=2):
+    draw = ImageDraw.Draw(image)
+    for bound in bounds:
+        # 🧙‍♂️ Drawing magic rectangles
+        p0, p1, p2, p3 = bound[0]
+        draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
+    return image
+
+# 🔮 The core function that does the OCR wizardry
+def inference(img, lang):
+    # 🕵️‍♂️ Reading the image, please hold...
+    reader = easyocr.Reader(lang)
+    bounds = reader.readtext(img.name)
+    im = Image.open(img.name)
+    draw_boxes(im, bounds)
+    im.save('result.jpg')
+    return ['result.jpg', pd.DataFrame(bounds).iloc[:, 1:]]
+
+# 🚀 Time to set up the Gradio app!
+def main():
+    title = '🖼️ Image to Multilingual OCR 👁️ with Gradio'
+    description = 'Multilingual OCR that works conveniently on all devices in multiple languages. 🌐'
+
+    examples = [
+        ['20-Books.jpg', ['en']],
+        ['COVID.png', ['en']],
+        ['chinese.jpg', ['ch_sim', 'en']],
+        ['japanese.jpg', ['ja', 'en']],
+        ['Hindi.jpeg', ['hi', 'en']]
+    ]
+
+    css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
+    choices = ["ch_sim", "ch_tra", "de", "en", "es", "ja", "hi", "ru"]
+
+    with gr.Blocks(css=css) as demo:
+        gr.Markdown(f"# {title}\n\n{description}")
+        
+        with gr.Row():
+            with gr.Column():
+                img_input = gr.Image(type='file', label='📥 Input Image')
+                lang_input = gr.CheckboxGroup(choices, value=['en'], label='🗣️ Language(s)')
+                submit_btn = gr.Button("Start OCR 🕵️‍♂️")
+            with gr.Column():
+                img_output = gr.Image(type='file', label='📤 Output Image')
+                df_output = gr.Dataframe(headers=['Text', 'Confidence'])
+
+        gr.Examples(
+            examples=examples,
+            inputs=[img_input, lang_input],
+            outputs=[img_output, df_output],
+            examples_per_page=5,
+            cache_examples=False
+        )
+
+        submit_btn.click(fn=inference, inputs=[img_input, lang_input], outputs=[img_output, df_output])
+
+    demo.launch(debug=True)
+
+if __name__ == "__main__":
+    download_sample_images()
+    main()