Update app.py

app.py

@@ -21,7 +21,9 @@ def detect_book_regions(image: np.ndarray, min_area=10000, eps_coef=0.02):
     kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
     closed = cv2.morphologyEx(edges, cv2.MORPH_CLOSE, kernel)
 
-    contours, _ = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    contours, _ = cv2.findContours(
+        closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
+    )
     boxes = []
 
     for cnt in contours:
@@ -98,7 +100,7 @@ def query_openlibrary(title_text: str, author_text: str = None):
 def process_image(image_file):
     """
     Gradio passes a PIL image or numpy array. Convert to OpenCV BGR, detect covers → OCR → OpenLibrary.
-    Return a DataFrame and CSV bytes (as raw bytes).
+    Return a DataFrame and a (filename, bytes) tuple for CSV.
     """
     img = np.array(image_file)[:, :, ::-1].copy()  # PIL to OpenCV BGR
     boxes = detect_book_regions(img)
@@ -126,15 +128,10 @@ def process_image(image_file):
                 }
             )
 
-    # Build DataFrame
-    if not records:
-        df_empty = pd.DataFrame(columns=["title", "author_name", "publisher", "first_publish_year"])
-        csv_bytes = df_empty.to_csv(index=False).encode()
-        return df_empty, csv_bytes
-
-    df = pd.DataFrame(records)
+    # Build DataFrame (even if empty)
+    df = pd.DataFrame(records, columns=["title", "author_name", "publisher", "first_publish_year"])
     csv_bytes = df.to_csv(index=False).encode()
-    return df, csv_bytes
+    return df, ("books.csv", csv_bytes)
 
 # ──────────────────────────────────────────────────────────────
 # 5. Build the Gradio Interface
@@ -162,9 +159,8 @@ def build_interface():
         download_file = gr.File(label="Download CSV")
 
         def on_run(image):
-            df, csv_bytes = process_image(image)
-            # Return DataFrame plus a dict that gr.File understands:
-            return df, {"name": "books.csv", "data": csv_bytes}
+            df, file_tuple = process_image(image)
+            return df, file_tuple
 
         run_button.click(
             fn=on_run,
@@ -176,5 +172,4 @@ def build_interface():
 
 if __name__ == "__main__":
     demo_app = build_interface()
-    # You can add share=True if you want a public link; otherwise this is fine:
-    demo_app.launch()
+    demo_app.launch()