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import spaces
import gradio as gr
import fitz # PyMuPDF
from PIL import Image
import pytesseract
def clean_ocr_text(text):
lines = text.splitlines()
cleaned_lines = []
for line in lines:
line = line.strip()
if line and not line.isspace():
cleaned_lines.append(line)
return "\n".join(cleaned_lines)
def extract_text_markdown(doc):
markdown_output = ""
image_counter = 1
for page_num, page in enumerate(doc):
blocks = page.get_text("dict")["blocks"]
elements = []
for b in blocks:
y = b["bbox"][1]
if b["type"] == 0: # Texto
for line in b["lines"]:
line_y = line["bbox"][1]
line_text = " ".join([span["text"] for span in line["spans"]]).strip()
max_font_size = max([span.get("size", 10) for span in line["spans"]])
if line_text:
elements.append((line_y, line_text, max_font_size))
elif b["type"] == 1: # Imagen
try:
image = page.get_pixmap(matrix=fitz.Matrix(2, 2), clip=b["bbox"])
image_path = f"/tmp/imagen_embebida_{page_num + 1}_{image_counter}.jpg"
image.save(image_path)
elements.append((y, f"", 10))
image_counter += 1
except Exception as e:
elements.append((y, f"[Error al procesar imagen: {e}]", 10))
elements.sort(key=lambda x: x[0])
previous_y = None
for y, text, font_size in elements:
is_header = font_size >= 14
if previous_y is not None and abs(y - previous_y) > 10:
markdown_output += "\n"
if is_header:
markdown_output += f"\n### {text.strip()}\n"
else:
markdown_output += text.strip() + "\n"
previous_y = y
markdown_output += "\n---\n\n"
return markdown_output.strip()
@spaces.GPU
def convert(pdf_file):
doc = fitz.open(pdf_file)
markdown_output = ""
image_counter = 1
image_paths = []
for page_num in range(len(doc)):
page = doc[page_num]
text = page.get_text("text").strip()
if len(text) > 30:
# Página con texto normal
markdown_output += extract_text_markdown([page]) + "\n"
else:
# Página vacía o con imagen: hacer OCR
pix = page.get_pixmap(dpi=300)
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
# Guardar imagen completa
image_path = f"/tmp/ocr_page_{page_num + 1}.jpg"
img.save(image_path)
image_paths.append(image_path)
markdown_output += f"\n"
try:
ocr_text = pytesseract.image_to_string(img, lang="spa")
except pytesseract.TesseractError:
ocr_text = pytesseract.image_to_string(img) # fallback sin lang
ocr_text = clean_ocr_text(ocr_text)
if ocr_text.strip():
markdown_output += ocr_text + "\n"
markdown_output += "\n---\n\n"
return markdown_output.strip(), {}, image_paths
gr.Interface(
fn=convert,
inputs=[gr.File(label="Sube tu PDF", type="filepath")],
outputs=[
gr.Text(label="Markdown estructurado"),
gr.JSON(label="Metadata"),
gr.Gallery(label="Imágenes extraídas")
],
).launch()
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