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Update app.py
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app.py
CHANGED
@@ -2,7 +2,7 @@ import os
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import re
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import io
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import streamlit as st
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from PIL import Image, ImageDraw
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from google import genai
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from google.genai import types
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from pdf2image import convert_from_bytes
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@@ -15,6 +15,8 @@ Only return the list, nothing else. Example:
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[[0.05, 0.12, 0.25, 0.18], [0.30, 0.40, 0.50, 0.55]]
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"""
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def parse_list_boxes(text):
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"""Improved parsing with better error handling"""
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try:
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@@ -24,25 +26,65 @@ def parse_list_boxes(text):
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return [[float(x) for x in m] for m in matches]
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def draw_bounding_boxes(image, boxes):
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"""Enhanced drawing with
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if not boxes:
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return image
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draw = ImageDraw.Draw(image)
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width, height = image.size
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for box in boxes:
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try:
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xmin = max(0.0, min(1.0, box[0])) * width
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ymin = max(0.0, min(1.0, box[1])) * height
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xmax = max(0.0, min(1.0, box[2])) * width
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ymax = max(0.0, min(1.0, box[3])) * height
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draw.rectangle([xmin, ymin, xmax, ymax], outline="#00FF00", width=3)
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except Exception as e:
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st.error(f"Error drawing box: {str(e)}")
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return image
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# Streamlit UI
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st.title("PDF Text Detection")
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uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
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@@ -53,7 +95,6 @@ if uploaded_file and st.button("Analyze"):
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images = convert_from_bytes(uploaded_file.read(), dpi=300)
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client = genai.Client(api_key=os.getenv("KEY"))
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# Create tabs for pages
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tabs = st.tabs([f"Page {i+1}" for i in range(len(images))])
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for idx, (tab, image) in enumerate(zip(tabs, images)):
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@@ -61,13 +102,12 @@ if uploaded_file and st.button("Analyze"):
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col1, col2 = st.columns(2)
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with col1:
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st.image(image, caption="Original",
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with col2:
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img_byte_arr = io.BytesIO()
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image.save(img_byte_arr, format='PNG')
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# Get bounding boxes
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response = client.models.generate_content(
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model="gemini-2.0-flash-exp",
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contents=[
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@@ -79,14 +119,21 @@ if uploaded_file and st.button("Analyze"):
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]
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)
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# Parse and draw
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boxes = parse_list_boxes(response.text)
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st.image(annotated,
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caption=f"Detected {len(boxes)} text regions",
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# Debug section
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debug_expander = st.expander("Debug Details")
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with debug_expander:
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import re
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import io
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import streamlit as st
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from PIL import Image, ImageDraw, ImageFont
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from google import genai
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from google.genai import types
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from pdf2image import convert_from_bytes
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[[0.05, 0.12, 0.25, 0.18], [0.30, 0.40, 0.50, 0.55]]
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"""
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TEXT_EXTRACTION_PROMPT = "Extract the text in this image. Return only the exact text, nothing else."
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def parse_list_boxes(text):
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"""Improved parsing with better error handling"""
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try:
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return [[float(x) for x in m] for m in matches]
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def draw_bounding_boxes(image, boxes):
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"""Enhanced drawing with numbering"""
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if not boxes:
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return image
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draw = ImageDraw.Draw(image)
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width, height = image.size
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for i, box in enumerate(boxes):
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try:
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# Convert normalized coordinates to pixel values
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xmin = max(0.0, min(1.0, box[0])) * width
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ymin = max(0.0, min(1.0, box[1])) * height
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xmax = max(0.0, min(1.0, box[2])) * width
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ymax = max(0.0, min(1.0, box[3])) * height
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# Draw bounding box
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draw.rectangle([xmin, ymin, xmax, ymax], outline="#00FF00", width=3)
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# Draw number label
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label = str(i+1)
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draw.text((xmin + 5, ymin + 5), label, fill="red")
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except Exception as e:
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st.error(f"Error drawing box: {str(e)}")
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return image
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def extract_text_from_region(client, image, box):
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"""Extract text from a specific region using Gemini"""
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try:
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width, height = image.size
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# Convert normalized coordinates to pixel values
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xmin = int(max(0.0, min(1.0, box[0])) * width)
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ymin = int(max(0.0, min(1.0, box[1])) * height)
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xmax = int(max(0.0, min(1.0, box[2])) * width)
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ymax = int(max(0.0, min(1.0, box[3])) * height)
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if xmin >= xmax or ymin >= ymax:
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return ""
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# Crop and convert to bytes
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cropped = image.crop((xmin, ymin, xmax, ymax))
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img_byte_arr = io.BytesIO()
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cropped.save(img_byte_arr, format='PNG')
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# Call Gemini API
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response = client.models.generate_content(
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model="gemini-2.0-flash-exp",
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contents=[
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TEXT_EXTRACTION_PROMPT,
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types.Part.from_bytes(
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data=img_byte_arr.getvalue(),
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mime_type="image/png"
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)
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]
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)
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return response.text.strip()
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except Exception as e:
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st.error(f"Text extraction error: {str(e)}")
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return ""
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# Streamlit UI
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st.title("PDF Text Detection")
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uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
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images = convert_from_bytes(uploaded_file.read(), dpi=300)
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client = genai.Client(api_key=os.getenv("KEY"))
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tabs = st.tabs([f"Page {i+1}" for i in range(len(images))])
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for idx, (tab, image) in enumerate(zip(tabs, images)):
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col1, col2 = st.columns(2)
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with col1:
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st.image(image, caption="Original", use_column_width=True)
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with col2:
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# Get bounding boxes
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img_byte_arr = io.BytesIO()
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image.save(img_byte_arr, format='PNG')
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response = client.models.generate_content(
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model="gemini-2.0-flash-exp",
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contents=[
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]
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)
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boxes = parse_list_boxes(response.text)
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texts = [extract_text_from_region(client, image, box) for box in boxes]
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# Draw annotated image
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annotated = draw_bounding_boxes(image.copy(), boxes)
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st.image(annotated,
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caption=f"Detected {len(boxes)} text regions",
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use_column_width=True)
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# Display extracted texts
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if any(texts):
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st.subheader("Extracted Texts:")
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for i, text in enumerate(texts, 1):
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st.write(f"{i}. {text if text else 'No text detected'}")
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# Debug section
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debug_expander = st.expander("Debug Details")
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with debug_expander:
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