Update app.py

app.py

@@ -1,48 +1,48 @@
-import pytesseract
-from PIL import Image
-import gradio as gr
-import re
-
-pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
-
-def perform_ocr(image):
-    text = pytesseract.image_to_string(image, lang='hin+eng')
-    return text
-
-def search_first_keyword_in_text(text, keyword):
-    if keyword:
-        text = text.replace('\n', ' ')
-        sentences = re.split(r'(?<=[.!?]) +', text)
-        for sentence in sentences:
-            if re.search(keyword, sentence, re.IGNORECASE):
-                highlighted_sentence = re.sub(f'({re.escape(keyword)})', r'<b>\1</b>', sentence, flags=re.IGNORECASE)
-                return highlighted_sentence.strip()
-        return "No matching sentence found."
-    else:
-        return "Please enter a keyword to search."
-
-def ocr_and_search(image, keyword):
-    try:
-        extracted_text = perform_ocr(image)
-        search_result = search_first_keyword_in_text(extracted_text, keyword)
-        return extracted_text, search_result
-    except Exception as e:
-        return str(e), str(e)
-
-def web_app():
-    interface = gr.Interface(
-        fn=ocr_and_search,
-        inputs=[
-            gr.Image(type="pil", label="Upload Image"),
-            gr.Textbox(placeholder="Enter keyword to search", label="Keyword Search")
-        ],
-        outputs=[
-            gr.Textbox(label="Extracted Text", lines=10),
-            gr.HTML(label="Search Result (First Matching Sentence)")
-        ],
-        title="OCR and Keyword Search Application"
-    )
-    interface.launch()
-
-if __name__ == "__main__":
-    web_app()
+import gradio as gr
+from transformers import pipeline
+import re
+
+# Load a publicly available OCR pipeline (make sure this model exists)
+ocr_pipeline = pipeline("image-to-text", model="microsoft/vision-ocr")
+
+def perform_ocr(image):
+    text = ocr_pipeline(image)[0]['generated_text']
+    return text
+
+def search_first_keyword_in_text(text, keyword):
+    if keyword:
+        text = text.replace('\n', ' ')
+        sentences = re.split(r'(?<=[.!?]) +', text)
+        for sentence in sentences:
+            if re.search(keyword, sentence, re.IGNORECASE):
+                highlighted_sentence = re.sub(f'({re.escape(keyword)})', r'<b>\1</b>', sentence, flags=re.IGNORECASE)
+                return highlighted_sentence.strip()
+        return "No matching sentence found."
+    else:
+        return "Please enter a keyword to search."
+
+def ocr_and_search(image, keyword):
+    try:
+        extracted_text = perform_ocr(image)
+        search_result = search_first_keyword_in_text(extracted_text, keyword)
+        return extracted_text, search_result
+    except Exception as e:
+        return str(e), str(e)
+
+def web_app():
+    interface = gr.Interface(
+        fn=ocr_and_search,
+        inputs=[
+            gr.Image(type="pil", label="Upload Image"),
+            gr.Textbox(placeholder="Enter keyword to search", label="Keyword Search")
+        ],
+        outputs=[
+            gr.Textbox(label="Extracted Text", lines=10),
+            gr.HTML(label="Search Result (First Matching Sentence)")
+        ],
+        title="OCR and Keyword Search Application"
+    )
+    interface.launch()
+
+if __name__ == "__main__":
+    web_app()