changes

app.py

@@ -632,9 +632,11 @@ def _html_escape(s: str) -> str:
 # ----------------------------------------------------------------------
 # Main OCR wrapper for Gradio
 #
+import tempfile
+
 def run_ocr(image, xml_file, apply_gray, apply_bin, highlight_metric):
     if image is None:
-        return None, "", None
+        return None, "", None, "", None, None
 
     pil_img = Image.fromarray(image).convert("RGB")
     if apply_gray:
@@ -688,7 +690,22 @@ def run_ocr(image, xml_file, apply_gray, apply_bin, highlight_metric):
         predicted_html = seg_html
 
     overlay_img = draw_boxes(pil_img, boxes) if boxes else pil_img
-    return overlay_img, predicted_html, df_all
+
+    # Clean text for editing (strip HTML)
+    clean_pred_text = re.sub(r"<[^>]+>", "", predicted_html)
+
+    # Save outputs to temporary files
+    tmp_dir = tempfile.mkdtemp()
+    txt_path = os.path.join(tmp_dir, "ocr_prediction.txt")
+    csv_path = os.path.join(tmp_dir, "token_scores.csv")
+
+    with open(txt_path, "w", encoding="utf-8") as f:
+        f.write(clean_pred_text)
+
+    if df_all is not None and not df_all.empty:
+        df_all.to_csv(csv_path, index=False, encoding="utf-8")
+
+    return overlay_img, predicted_html, df_all, clean_pred_text, txt_path, csv_path
 
 
 # ----------------------------------------------------------------------
@@ -721,14 +738,40 @@ def create_gradio_interface():
         predictions_output = gr.HTML(label="Predictions (HTML)")
         df_output = gr.DataFrame(label="Token Scores", interactive=False)
 
+        # 📝 Editable textbox for user corrections
+        editable_text = gr.Textbox(label="Edit Recognized Text", lines=8, interactive=True)
+
+        # 📁 Download buttons
+        download_text = gr.File(label="Download Edited Text (.txt)")
+        download_csv = gr.File(label="Download Token Scores (.csv)")
+
+        # Run OCR
         run_btn.click(
             fn=run_ocr,
             inputs=[image_input, xml_input, apply_gray_checkbox, apply_bin_checkbox, metric_radio],
-            outputs=[overlay_output, predictions_output, df_output],
+            outputs=[
+                overlay_output,
+                predictions_output,
+                df_output,
+                editable_text,
+                download_text,
+                download_csv,
+            ],
         )
 
-    return demo
+        # Function to save user-edited text
+        def save_edited_text(text):
+            import tempfile, os
+            tmp_dir = tempfile.mkdtemp()
+            path = os.path.join(tmp_dir, "edited_ocr_text.txt")
+            with open(path, "w", encoding="utf-8") as f:
+                f.write(text)
+            return path
 
+        # Update download file when user edits
+        editable_text.change(fn=save_edited_text, inputs=editable_text, outputs=download_text)
+
+    return demo
 
 
 if __name__ == "__main__":