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app.py

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+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+import pytesseract as tsr
+from PIL import Image
+
+import sys, os
+import gradio as gr
+
+tsr.pytesseract.tesseract_cmd = r'/usr/bin/tesseract'
+
+model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+
+def extractAndTranslate(image):
+    # Extract Text
+    extractedText = tsr.image_to_string(image, lang='eng+uzb')
+    extractedTextFormatted = ' '.join(extractedText.split('\n'))
+    
+    # Translate 
+    tokenizer.src_lang = "en"
+    encodedText = tokenizer(extractedTextFormatted, return_tensors="pt")
+    generatedTokens = model.generate(**encodedText, forced_bos_token_id=tokenizer.get_lang_id("uz"))
+    
+    return tokenizer.batch_decode(generatedTokens, skip_special_tokens=True)[0]
+
+demoApp = gr.Interface(extractAndTranslate, "image", "text")
+
+demoApp.launch()