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import gradio as gr
from mineru_vl_utils.mineru_client import MinerUClient
from PIL import Image
import fitz # PyMuPDF
import os
import torch
# Init client
model_path = "opendatalab/MinerU2.5-2509-1.2B"
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"⚡ Loading MinerU on device: {device}")
client = MinerUClient(backend="transformers", model_path=model_path)
def extract_from_file(file):
try:
print(f"📄 Processing file: {file.name}")
ext = os.path.splitext(file.name)[-1].lower()
images = []
if ext == ".pdf":
doc = fitz.open(file.name)
for i, page in enumerate(doc):
pix = page.get_pixmap()
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
images.append(img)
print(f"✅ Converted page {i+1} to image")
else:
images.append(Image.open(file.name))
results = []
for i, img in enumerate(images):
print(f"🔍 Extracting text from page {i+1}")
blocks = client.two_step_extract(img)
if not blocks:
print(f"⚠️ No blocks found on page {i+1}")
results.append("[EMPTY PAGE]")
continue
text_blocks = []
for b in blocks:
if hasattr(b, "text") and b.text:
text_blocks.append(b.text)
page_text = "\n".join(text_blocks) if text_blocks else "[NO TEXT FOUND]"
results.append(page_text)
print(f"✅ Page {i+1} extracted")
return "\n\n--- PAGE ---\n\n".join(results)
except Exception as e:
print(f"❌ ERROR: {e}")
return f"Error during extraction: {str(e)}"
demo = gr.Interface(
fn=extract_from_file,
inputs=gr.File(type="filepath", label="Upload PDF or Image"),
outputs=gr.Textbox(label="Extracted Text", lines=20),
title="MinerU2.5 Document Extractor",
description="Upload a PDF or Image to extract structured text using MinerU2.5."
)
demo.launch() |