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Update app.py
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app.py
CHANGED
@@ -4,8 +4,6 @@ import pytesseract
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import requests
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import pandas as pd
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import gradio as gr
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import io
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from io import BytesIO
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# 1. Utility: Detect rectangular contours (approximate book covers)
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@@ -100,7 +98,7 @@ def query_openlibrary(title_text: str, author_text: str = None):
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def process_image(image_file):
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"""
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Gradio passes a PIL image or numpy array. Convert to OpenCV BGR, detect covers β OCR β OpenLibrary.
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Return a DataFrame and
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"""
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img = np.array(image_file)[:, :, ::-1].copy() # PIL to OpenCV BGR
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boxes = detect_book_regions(img)
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@@ -128,19 +126,15 @@ def process_image(image_file):
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}
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)
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if not records:
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df_empty = pd.DataFrame(columns=["title", "author_name", "publisher", "first_publish_year"])
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buffer = io.BytesIO(empty_csv)
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buffer.name = "books.csv"
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return df_empty, buffer
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df = pd.DataFrame(records)
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csv_bytes = df.to_csv(index=False).encode()
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buffer.name = "books.csv"
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return df, buffer
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# 5. Build the Gradio Interface
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@@ -168,8 +162,9 @@ def build_interface():
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download_file = gr.File(label="Download CSV")
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def on_run(image):
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df,
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run_button.click(
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fn=on_run,
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@@ -181,4 +176,5 @@ def build_interface():
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if __name__ == "__main__":
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demo_app = build_interface()
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demo_app.launch()
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import requests
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import pandas as pd
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import gradio as gr
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# 1. Utility: Detect rectangular contours (approximate book covers)
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def process_image(image_file):
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"""
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Gradio passes a PIL image or numpy array. Convert to OpenCV BGR, detect covers β OCR β OpenLibrary.
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Return a DataFrame and CSV bytes (as raw bytes).
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"""
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img = np.array(image_file)[:, :, ::-1].copy() # PIL to OpenCV BGR
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boxes = detect_book_regions(img)
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}
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)
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# Build DataFrame
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if not records:
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df_empty = pd.DataFrame(columns=["title", "author_name", "publisher", "first_publish_year"])
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csv_bytes = df_empty.to_csv(index=False).encode()
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return df_empty, csv_bytes
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df = pd.DataFrame(records)
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csv_bytes = df.to_csv(index=False).encode()
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return df, csv_bytes
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# 5. Build the Gradio Interface
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download_file = gr.File(label="Download CSV")
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def on_run(image):
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df, csv_bytes = process_image(image)
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# Return DataFrame plus a dict that gr.File understands:
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return df, {"name": "books.csv", "data": csv_bytes}
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run_button.click(
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fn=on_run,
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if __name__ == "__main__":
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demo_app = build_interface()
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# You can add share=True if you want a public link; otherwise this is fine:
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demo_app.launch()
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