Update app.py

app.py

@@ -1,19 +1,36 @@
 import streamlit as st
+import io
+from PIL import Image
+import easyocr
 from transformers import pipeline
 
 # Create a text2text-generation pipeline with the "google/flan-t5-base" model
 pipe = pipeline("text2text-generation", model="google/flan-t5-base")
 
+# Initialize the EasyOCR reader for text extraction from images
+ocr_reader = easyocr.Reader(['en'])
+
 st.title("Text Explanation Model")
-user_text = st.text_area("Enter text:")
 
-if st.button("Generate Explanation"):
-    if user_text:
-        # Use the pipeline to generate an explanation for the input text
-        explanation = pipe(user_text, max_length=100, do_sample=True)[0]["generated_text"]
-        st.markdown("**Explanation:**")
+uploaded_file = st.file_uploader("Upload an image:")
+
+if uploaded_file is not None:
+    # Read the uploaded image
+    image = Image.open(uploaded_file)
+
+    # Extract text from the image using OCR
+    ocr_results = ocr_reader.readtext(image)
+    extracted_text = " ".join([res[1] for res in ocr_results])
+    st.markdown("**Extracted text:**")
+    st.markdown(extracted_text)
+
+    if extracted_text:
+        # Use the pipeline to generate a concise explanation
+        explanation = pipe(extracted_text, max_length=30, do_sample=True)[0]["generated_text"]
+        st.markdown("**Explanation (5-6 lines):**")
         st.markdown(explanation)
     else:
-        st.warning("Please enter text.")
+        st.warning("No text extracted from the image.")
 
-st.markdown("Use the 'Generate Explanation' button to generate an explanation for the provided text.")
+else:
+    st.markdown("Please upload an image to extract text and generate an explanation.")