Create app.py

app.py

@@ -0,0 +1,40 @@
+from PIL import Image
+import pytesseract
+import gradio as gr
+from transformers import pipeline
+
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def extract_and_summarize(image):
+    if image is None:
+        return "Please upload an image.", "No summary yet."
+
+    extracted_text = pytesseract.image_to_string(image).strip()
+    if not extracted_text:
+        return "No text detected in the image.", ""
+
+    if len(extracted_text.split()) > 30:
+        summary = summarizer(
+            extracted_text,
+            max_length=100,
+            min_length=30,
+            do_sample=False
+        )[0]['summary_text']
+    else:
+        summary = "Text too short for summarization."
+
+    return extracted_text, summary
+
+
+interface = gr.Interface(
+    fn=extract_and_summarize,
+    inputs=gr.Image(type="pil", label="Upload Image"),
+    outputs=[
+        gr.Textbox(label="Extracted Text"),
+        gr.Textbox(label="Summary"),
+    ],
+    title="🧠 OCR Text Extractor + Summarizer",
+    description="Upload an image with text — it extracts the text using Tesseract OCR and summarizes it using a transformer model."
+)
+
+interface.launch()