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GLM-OCR Hugging Face Space app for PDF/image OCR with header inclusion
and table-structure stabilization for downstream bank-statement pipelines.
Hard-coded knobs (no environment variables required).
Primary goal for reconcile rate:
- preserve right-most columns (often "Balance") by higher DPI render + right padding
- keep tables as tables (convert markdown pipe tables -> HTML table)
- return ---page-separator--- between pages
"""
# Patch asyncio first (before Gradio imports it) to suppress Python 3.13 cleanup noise
import asyncio
try:
_orig_close = asyncio.BaseEventLoop.close
def _safe_close(self):
try:
_orig_close(self)
except (ValueError, OSError):
pass
asyncio.BaseEventLoop.close = _safe_close
except Exception:
pass
import logging
import os
import re
import html
import tempfile
from typing import List, Tuple
import yaml
import gradio as gr
import glmocr
log = logging.getLogger("glmocr_app")
logging.basicConfig(level=logging.INFO)
GLMOCR_BASE = os.path.dirname(glmocr.__file__)
CONFIG_PATH = os.path.join(GLMOCR_BASE, "config.yaml")
FORMATTER_PATH = os.path.join(GLMOCR_BASE, "postprocess", "result_formatter.py")
# ============================================================
# HARD-CODED SETTINGS (edit these numbers to tune quality/speed)
# ============================================================
# 1) GLM-OCR MaaS API key
# IMPORTANT: Do NOT hard-code secrets in a public Space.
# If your Space is public, switch to HF Secrets instead.
GLMOCR_API_KEY = "e2b138b2005a41cb9d87dd18805838aa.lyd51L23rcDbsw0w"
# 2) Render quality (higher = better OCR for small/right-aligned digits; slower)
RENDER_SCALE = 2.2 # try 2.5 if Balance column is still missing
# 3) Add padding to protect columns near edges (Balance is usually right-most)
PAD_LEFT_FRAC = 0.02
PAD_RIGHT_FRAC = 0.06 # try 0.10 if right-most balances are missing
PAD_TOP_FRAC = 0.01
PAD_BOTTOM_FRAC = 0.01
# 4) Mild contrast boost (helps faint gray text)
ENABLE_CONTRAST = True
# 5) Header/footer band heuristics
DEFAULT_ZONE_FRAC = 0.12 # OCR band for header (top 12%) when regions not available
PDF_HEADER_BAND_FRAC = 0.10 # PDF text fallback: take top 10% words if clip returns empty
# Footer: disabled by default to avoid duplicating what GLM already returns
ENABLE_FOOTER_OCR = False
PDF_FOOTER_BAND_FRAC = 0.88 # bottom 12% (if footer enabled)
# MaaS minimum image sizes for crops; we pad if needed
MIN_CROP_HEIGHT = 112
MIN_CROP_PIXELS = 112 * 112
# ============================================================
# Single shared parser to avoid re-init per request
_parser = None
def get_parser():
global _parser
if _parser is None:
from glmocr import GlmOcr
_parser = GlmOcr(
api_key=GLMOCR_API_KEY,
mode="maas",
)
return _parser
# ---------------------------------------------------------------------------
# Best-effort config tweaks (safe to fail on read-only HF env)
# ---------------------------------------------------------------------------
try:
with open(CONFIG_PATH, "r") as f:
config = yaml.safe_load(f)
config["pipeline"]["maas"]["enabled"] = True
config["pipeline"]["maas"]["api_key"] = GLMOCR_API_KEY
with open(CONFIG_PATH, "w") as f:
yaml.dump(config, f, default_flow_style=False, sort_keys=False)
except Exception:
pass
# Best-effort formatter tweak: avoid stripping header/footer labels
try:
with open(FORMATTER_PATH, "r") as f:
source = f.read()
for label in ('"header"', "'header'", '"footer"', "'footer'", '"doc_header"', "'doc_header'", '"doc_footer"', "'doc_footer'"):
source = re.sub(r",\s*" + re.escape(label), "", source)
source = re.sub(re.escape(label) + r"\s*,", "", source)
source = re.sub(re.escape(label), "", source)
with open(FORMATTER_PATH, "w") as f:
f.write(source)
except Exception:
pass
# --------------------------
# Header/footer helpers
# --------------------------
def get_header_footer_zones(regions, norm_height=1000):
"""Infer header/footer extents from bbox regions if present."""
if not regions:
return None, None
y_tops, y_bottoms = [], []
for r in regions:
bbox = r.get("bbox_2d") if isinstance(r, dict) else getattr(r, "bbox_2d", None)
if bbox and len(bbox) >= 4:
y_tops.append(bbox[1])
y_bottoms.append(bbox[3])
if not y_tops:
return None, None
return min(y_tops) / norm_height, max(y_bottoms) / norm_height
def extract_zone_text_pdf(pdf_path, page_num, y_start_frac, y_end_frac):
"""Extract text from a horizontal band using a clip rect (works if PDF has text layer)."""
try:
import pymupdf as fitz
doc = fitz.open(pdf_path)
page = doc[page_num]
h, w = page.rect.height, page.rect.width
rect = fitz.Rect(0, h * y_start_frac, w, h * y_end_frac)
text = page.get_text(clip=rect).strip()
doc.close()
return text
except Exception:
return ""
def extract_pdf_text_in_band(pdf_path, page_num, y_start_frac, y_end_frac):
"""Extract words whose bbox intersects a vertical band (robust fallback)."""
try:
import pymupdf as fitz
doc = fitz.open(pdf_path)
page = doc[page_num]
h = page.rect.height
y_lo = h * y_start_frac
y_hi = h * y_end_frac
words = page.get_text("words")
doc.close()
parts = []
for w in words:
if len(w) >= 5:
y0, y1 = float(w[1]), float(w[3])
if y0 < y_hi and y1 > y_lo:
parts.append(w[4])
return " ".join(parts).strip()
except Exception:
return ""
def ocr_zone(image_path, y_start_frac, y_end_frac):
"""Run OCR on a horizontal band. Pads small crops to meet MaaS minimum size."""
zone_name = "header" if y_end_frac < 0.5 else "footer"
try:
from PIL import Image
img = Image.open(image_path).convert("RGB")
w, h = img.size
y0 = max(0, int(h * y_start_frac))
y1 = min(h, int(h * y_end_frac))
if y1 <= y0:
return ""
crop = img.crop((0, y0, w, y1))
cw, ch = crop.size
if ch < MIN_CROP_HEIGHT or (cw * ch) < MIN_CROP_PIXELS:
need_h = max(ch, MIN_CROP_HEIGHT)
need_w = max(cw, 1)
if (need_w * need_h) < MIN_CROP_PIXELS:
need_w = max(need_w, (MIN_CROP_PIXELS + need_h - 1) // need_h)
canvas = Image.new("RGB", (need_w, need_h), (255, 255, 255))
if zone_name == "header":
canvas.paste(crop, (0, 0))
else:
canvas.paste(crop, (0, need_h - ch))
crop = canvas
fd, path = tempfile.mkstemp(suffix=".jpg")
os.close(fd)
try:
crop.save(path, "JPEG", quality=92)
parser = get_parser()
out = parser.parse(path)
if not isinstance(out, list):
out = [out]
if out and getattr(out[0], "markdown_result", None):
return (out[0].markdown_result or "").strip()
finally:
try:
os.unlink(path)
except Exception:
pass
except Exception as e:
log.warning("[%s] ocr_zone failed: %s", zone_name, e, exc_info=True)
return ""
def fix_account_number(hdr: str) -> str:
"""Fix common account-number formatting issues."""
if not hdr:
return hdr
if "Account Number:" in hdr and "Account Number: " not in hdr:
m = re.search(r"[0-9]{5,}", hdr)
if m:
hdr = hdr.replace("Account Number:", "Account Number: " + m.group(0))
acct_match = re.search(r"Account Number: ([0-9]{5,})", hdr)
if acct_match:
acct = acct_match.group(1)
if hdr.startswith(acct):
hdr = hdr[len(acct):].lstrip()
return hdr
# --------------------------
# Table stabilization helpers
# --------------------------
def close_unclosed_html(md: str) -> str:
"""Close unclosed <table>/<tr>/<td> tags to prevent bleed."""
if not md:
return md
open_tags = re.findall(r"<(table|tbody|thead|tr|td|th)\b", md, flags=re.IGNORECASE)
close_tags = re.findall(r"</(table|tbody|thead|tr|td|th)>", md, flags=re.IGNORECASE)
def count(tags, name):
return sum(1 for t in tags if t.lower() == name)
for tag in reversed(["td", "th", "tr", "thead", "tbody", "table"]):
opened = count(open_tags, tag)
closed = count(close_tags, tag)
if opened > closed:
md += ("</%s>" % tag) * (opened - closed)
return md
def looks_like_markdown_table(block: str) -> bool:
"""Detect simple markdown pipe tables."""
lines = [ln.rstrip() for ln in block.strip().splitlines() if ln.strip()]
if len(lines) < 2:
return False
if "|" not in lines[0]:
return False
sep = lines[1].replace(" ", "")
return ("---" in sep) and ("|" in sep)
def md_table_to_html(block: str) -> str:
"""Convert a simple markdown pipe table to HTML table (best-effort)."""
lines = [ln.strip() for ln in block.strip().splitlines() if ln.strip()]
if len(lines) < 2:
return block
def split_row(row: str):
row = row.strip()
if row.startswith("|"):
row = row[1:]
if row.endswith("|"):
row = row[:-1]
return [p.strip() for p in row.split("|")]
header = split_row(lines[0])
body_lines = [ln for ln in lines[2:] if "|" in ln]
html_rows = []
html_rows.append("<tr>" + "".join(f"<th>{html.escape(c)}</th>" for c in header) + "</tr>")
for ln in body_lines:
cols = split_row(ln)
if len(cols) < len(header):
cols += [""] * (len(header) - len(cols))
html_rows.append("<tr>" + "".join(f"<td>{html.escape(c)}</td>" for c in cols[:len(header)]) + "</tr>")
return "<table>\n" + "\n".join(html_rows) + "\n</table>"
def normalize_money_glyphs(text: str) -> str:
"""Conservative normalization for OCR number quirks."""
if not text:
return text
t = text.replace("−", "-").replace("–", "-").replace("—", "-")
t = re.sub(r"\(\s*\$?\s*([0-9]{1,3}(?:,[0-9]{3})*|[0-9]+)(\.[0-9]{2})\s*\)", r"-\1\2", t)
def o_to_zero(m):
token = m.group(0)
return token.replace("O", "0").replace("o", "0")
t = re.sub(r"\b[0-9Oo\$,.\-]{4,}\b", o_to_zero, t)
return t
def stabilize_tables_and_text(page_md: str) -> str:
"""Convert markdown pipe tables to HTML and close tags."""
if not page_md:
return page_md
page_md = normalize_money_glyphs(page_md)
blocks = re.split(r"\n\s*\n", page_md.strip())
out_blocks = []
for b in blocks:
if looks_like_markdown_table(b):
out_blocks.append(md_table_to_html(b))
else:
out_blocks.append(b)
stabilized = "\n\n".join(out_blocks)
return close_unclosed_html(stabilized)
# --------------------------
# PDF rendering with padding (critical for Balance column)
# --------------------------
def render_pdf_pages_to_images(pdf_path: str) -> Tuple[List[str], List[int]]:
import pymupdf as fitz
from PIL import Image, ImageEnhance
doc = fitz.open(pdf_path)
page_images: List[str] = []
page_heights: List[int] = []
for i in range(len(doc)):
page = doc[i]
pix = page.get_pixmap(matrix=fitz.Matrix(RENDER_SCALE, RENDER_SCALE), alpha=False)
img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
if ENABLE_CONTRAST:
img = ImageEnhance.Contrast(img).enhance(1.12)
w, h = img.size
pad_l = int(w * PAD_LEFT_FRAC)
pad_r = int(w * PAD_RIGHT_FRAC)
pad_t = int(h * PAD_TOP_FRAC)
pad_b = int(h * PAD_BOTTOM_FRAC)
if any(p > 0 for p in (pad_l, pad_r, pad_t, pad_b)):
canvas = Image.new("RGB", (w + pad_l + pad_r, h + pad_t + pad_b), (255, 255, 255))
canvas.paste(img, (pad_l, pad_t))
img = canvas
img_path = os.path.join(tempfile.gettempdir(), f"glmocr_page_{os.getpid()}_{i}.png")
img.save(img_path, "PNG", compress_level=6)
page_images.append(img_path)
page_heights.append(img.height)
doc.close()
return page_images, page_heights
# --------------------------
# GLM-OCR result extraction
# --------------------------
def get_page_md_and_regions(page_result):
md = ""
if hasattr(page_result, "markdown_result") and page_result.markdown_result:
md = (page_result.markdown_result or "").strip()
regions = []
if hasattr(page_result, "json_result"):
jr = page_result.json_result
if isinstance(jr, dict) and "regions" in jr:
regions = jr.get("regions") or []
elif isinstance(jr, list) and len(jr) > 0:
r = jr[0] if isinstance(jr[0], list) else jr
if isinstance(r, list):
regions = r
elif isinstance(r, dict) and "regions" in r:
regions = r.get("regions") or []
return md, regions
# --------------------------
# Main entry
# --------------------------
def run_ocr(uploaded_file):
if uploaded_file is None:
return "Please upload a file."
page_images = []
try:
path = uploaded_file.name if hasattr(uploaded_file, "name") else str(uploaded_file)
is_pdf = path.lower().endswith(".pdf")
parser = get_parser()
page_heights = []
if is_pdf:
page_images, page_heights = render_pdf_pages_to_images(path)
results = parser.parse(page_images)
else:
page_images = [path]
page_heights = [1000]
results = parser.parse(path)
if not isinstance(results, list):
results = [results]
all_pages = []
for page_num, page_result in enumerate(results):
page_md, regions = get_page_md_and_regions(page_result)
img_h = page_heights[page_num] if page_num < len(page_heights) else 1000
header_end_frac, footer_start_frac = get_header_footer_zones(regions, img_h)
he = header_end_frac if header_end_frac is not None else DEFAULT_ZONE_FRAC
fs = footer_start_frac if footer_start_frac is not None else (1.0 - DEFAULT_ZONE_FRAC)
# clamp
he = max(0.02, min(0.25, he))
fs = max(0.75, min(0.98, fs))
parts = []
# Header inclusion: PDF text -> band words -> OCR band
hdr = ""
if is_pdf:
hdr = extract_zone_text_pdf(path, page_num, 0, he)
if not (hdr and hdr.strip()):
hdr = extract_pdf_text_in_band(path, page_num, 0, PDF_HEADER_BAND_FRAC)
if not (hdr and hdr.strip()) and page_num < len(page_images):
hdr = ocr_zone(page_images[page_num], 0, he)
if hdr and hdr.strip():
parts.append(fix_account_number(normalize_money_glyphs(hdr.strip())))
# Main OCR markdown, stabilized
if page_md and page_md.strip():
parts.append(stabilize_tables_and_text(page_md.strip()))
# Optional footer
if ENABLE_FOOTER_OCR and page_num < len(page_images):
ftr = ""
if is_pdf:
ftr = extract_zone_text_pdf(path, page_num, fs, 1.0)
if not (ftr and ftr.strip()):
ftr = extract_pdf_text_in_band(path, page_num, PDF_FOOTER_BAND_FRAC, 1.0)
if not (ftr and ftr.strip()):
ftr = ocr_zone(page_images[page_num], fs, 1.0)
if ftr and ftr.strip():
parts.append(normalize_money_glyphs(ftr.strip()))
if parts:
all_pages.append("\n\n".join(parts))
return "\n\n---page-separator---\n\n".join(all_pages) if all_pages else "(No content)"
except Exception as e:
import traceback
log.exception("run_ocr failed: %s", e)
return f"Error: {e}\n\n{traceback.format_exc()}"
finally:
# cleanup rendered images
for p in page_images:
try:
if isinstance(p, str) and p.endswith(".png") and "glmocr_page_" in os.path.basename(p):
os.unlink(p)
except Exception:
pass
with gr.Blocks(title="GLM-OCR") as demo:
gr.Markdown("# GLM-OCR\nUpload a PDF or image. Headers included; tables stabilized.")
file_in = gr.File(label="Upload PDF or image", file_types=[".pdf", ".png", ".jpg", ".jpeg", ".tiff", ".bmp"])
run_btn = gr.Button("Run OCR", variant="primary")
out = gr.Textbox(lines=40, label="Output (markdown)")
run_btn.click(fn=run_ocr, inputs=file_in, outputs=out)
if __name__ == "__main__":
demo.launch() |