Create app.py

app.py

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+import gradio as gr
+import os
+import shutil
+import fitz
+from PIL import Image
+import numpy as np
+import cv2
+import pytesseract
+from pytesseract import Output
+import zipfile
+from pdf2image import convert_from_path
+
+# [Keep all the helper functions from the original code]
+def convert_to_rgb(image_path):
+    img = Image.open(image_path)
+    rgb_img = img.convert("RGB")
+    return rgb_img
+
+def preprocess_image(image):
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
+    denoised = cv2.fastNlMeansDenoising(binary, None, 30, 7, 21)
+    resized = cv2.resize(denoised, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)
+    return resized
+
+def extract_vertical_blocks(image):
+    image_np = np.array(image)
+    data = pytesseract.image_to_data(image_np, lang='fra', output_type=Output.DICT)
+
+    blocks = []
+    current_block = ""
+    current_block_coords = [float('inf'), float('inf'), 0, 0]
+    last_bottom = -1
+    line_height = 0
+
+    for i in range(len(data['text'])):
+        if int(data['conf'][i]) > 0:
+            text = data['text'][i]
+            x, y, w, h = data['left'][i], data['top'][i], data['width'][i], data['height'][i]
+
+            if line_height == 0:
+                line_height = h * 1.2
+
+            if y > last_bottom + line_height:
+                if current_block:
+                    blocks.append({
+                        "text": current_block.strip(),
+                        "coords": current_block_coords
+                    })
+                    current_block = ""
+                    current_block_coords = [float('inf'), float('inf'), 0, 0]
+
+            current_block += text + " "
+            current_block_coords[0] = min(current_block_coords[0], x)
+            current_block_coords[1] = min(current_block_coords[1], y)
+            current_block_coords[2] = max(current_block_coords[2], x + w)
+            current_block_coords[3] = max(current_block_coords[3], y + h)
+
+            last_bottom = y + h
+
+    if current_block:
+        blocks.append({
+            "text": current_block.strip(),
+            "coords": current_block_coords
+        })
+
+    return blocks
+
+def draw_blocks_on_image(image_path, blocks, output_path):
+    image = cv2.imread(image_path)
+    for block in blocks:
+        coords = block['coords']
+        cv2.rectangle(image, (coords[0], coords[1]), (coords[2], coords[3]), (0, 0, 255), 2)
+    cv2.imwrite(output_path, image)
+    return output_path
+
+def process_image(image, output_folder, page_number):
+    image = convert_to_rgb(image)
+    blocks = extract_vertical_blocks(image)
+    base_name = f'page_{page_number + 1}.png'
+    image_path = os.path.join(output_folder, base_name)
+    image.save(image_path)
+    annotated_image_path = os.path.join(output_folder, f'annotated_{base_name}')
+    annotated_image_path = draw_blocks_on_image(image_path, blocks, annotated_image_path)
+    return blocks, annotated_image_path
+
+def save_extracted_text(blocks, page_number, output_folder):
+    text_file_path = os.path.join(output_folder, 'extracted_text.txt')
+    with open(text_file_path, 'a', encoding='utf-8') as f:
+        f.write(f"[PAGE {page_number}]\n")
+        for block in blocks:
+            f.write(block['text'] + "\n")
+        f.write(f"[FIN DE PAGE {page_number}]\n\n")
+    return text_file_path
+
+# Modified process_pdf function with better temp file handling
+def process_pdf(pdf_file):
+    # Create unique temporary working directory
+    temp_dir = os.path.join(os.getcwd(), "temp_processing")
+    output_dir = os.path.join(temp_dir, 'output_images')
+
+    # Clean up any existing temp directories
+    if os.path.exists(temp_dir):
+        shutil.rmtree(temp_dir)
+
+    os.makedirs(output_dir, exist_ok=True)
+
+    try:
+        # Convert PDF to images
+        images = convert_from_path(pdf_file.name)
+
+        # Process each image
+        annotated_images = []
+        for i, img in enumerate(images):
+            # Save temporary image
+            temp_img_path = os.path.join(temp_dir, f'temp_page_{i}.png')
+            img.save(temp_img_path)
+
+            # Process the image
+            blocks, annotated_image_path = process_image(temp_img_path, output_dir, i)
+            annotated_images.append(annotated_image_path)
+            save_extracted_text(blocks, i + 1, output_dir)
+
+        # Create ZIP file of annotated images
+        zip_path = os.path.join(temp_dir, "annotated_images.zip")
+        with zipfile.ZipFile(zip_path, 'w') as zipf:
+            for img_path in annotated_images:
+                zipf.write(img_path, os.path.basename(img_path))
+
+        # Get the text file
+        text_file_path = os.path.join(output_dir, 'extracted_text.txt')
+
+        # Read the files into memory before cleanup
+        with open(text_file_path, 'rb') as f:
+            text_content = f.read()
+        with open(zip_path, 'rb') as f:
+            zip_content = f.read()
+
+        return (text_file_path, zip_path)
+
+    except Exception as e:
+        raise gr.Error(f"Error processing PDF: {str(e)}")
+
+    finally:
+        # Clean up will be handled by Hugging Face Spaces
+        pass
+
+# Create Gradio interface with theme and better styling
+css = """
+.gradio-container {
+    font-family: 'IBM Plex Sans', sans-serif;
+}
+.gr-button {
+    color: white;
+    border-radius: 8px;
+    background: linear-gradient(45deg, #7928CA, #FF0080);
+    border: none;
+}
+"""
+
+# Create Gradio interface
+demo = gr.Interface(
+    fn=process_pdf,
+    inputs=[
+        gr.File(
+            label="Upload PDF Document",
+            file_types=[".pdf"],
+            type="filepath"
+        )
+    ],
+    outputs=[
+        gr.File(label="Extracted Text (TXT)"),
+        gr.File(label="Annotated Images (ZIP)")
+    ],
+    title="PDF Text Extraction and Annotation",
+    description="""
+    Upload a PDF document to:
+    1. Extract text content
+    2. Get annotated images showing detected text blocks
+
+    Supports multiple pages and French language text.
+    """,
+    article="Created by [Your Name] - [Your GitHub/Profile Link]",
+    css=css,
+    examples=[],  # Add example PDFs if you have any
+    cache_examples=False,
+    theme=gr.themes.Soft()
+)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()