"""German-OCR · GOCR — Demo (CPU), im german-ocr.de-Look. Moderner OCR-Viewer: buntes Box-Overlay + Maske + Text-Layout + strukturiertes JSON. Nutzt das eigene g_ocr-Paket (from_pretrained). Schnell, CPU, kein GPU. """ import os import json import time import numpy as np from PIL import Image, ImageDraw, ImageFont import gradio as gr import matplotlib.font_manager as fm import g_ocr _HERE = os.path.dirname(os.path.abspath(__file__)) EXAMPLES_DIR = os.path.join(_HERE, "examples") _FONT_PATH = fm.findfont("DejaVu Sans") WEBSITE = "https://german-ocr.de" LOGO = "https://german-ocr.de/icon.png" ocr = g_ocr.from_pretrained(drop_score=0.4) ocr.read(np.zeros((64, 64, 3), np.uint8)) # warmup # Lebendige, gut unterscheidbare Farben (eine pro Region) PALETTE = [ (230, 25, 75), (60, 180, 75), (0, 130, 200), (245, 130, 48), (145, 30, 180), (0, 158, 115), (240, 50, 230), (0, 114, 178), (213, 94, 0), (204, 121, 167), (86, 180, 233), (170, 110, 40), (0, 128, 128), (128, 0, 0), (75, 175, 60), ] _font_cache = {} def _font(sz): sz = int(max(10, min(42, sz))) if sz not in _font_cache: try: _font_cache[sz] = ImageFont.truetype(_FONT_PATH, sz) except Exception: _font_cache[sz] = ImageFont.load_default() return _font_cache[sz] def _col(i): return PALETTE[i % len(PALETTE)] def _pts(r): return [(int(x), int(y)) for x, y in r["quad"]] def _overlay(rgb, regions): """Original + buntes Box-Overlay (je Region eigene Farbe, halbtransparente Füllung).""" base = Image.fromarray(rgb).convert("RGBA") ov = Image.new("RGBA", base.size, (0, 0, 0, 0)) d = ImageDraw.Draw(ov) for i, r in enumerate(regions): c = _col(i) p = _pts(r) d.polygon(p, fill=c + (46,)) d.line(p + [p[0]], fill=c + (255,), width=3, joint="curve") return np.array(Image.alpha_composite(base, ov).convert("RGB")) def _mask(shape, regions): """Detektions-Maske: erkannte Regionen weiß auf schwarz.""" h, w = shape[:2] im = Image.new("RGB", (w, h), (0, 0, 0)) d = ImageDraw.Draw(im) for r in regions: d.polygon(_pts(r), fill=(255, 255, 255)) return np.array(im) def _textlayout(shape, regions): """Erkannte Werte farbig an Originalposition (weißes Blatt).""" h, w = shape[:2] im = Image.new("RGB", (w, h), (255, 255, 255)) d = ImageDraw.Draw(im) for i, r in enumerate(regions): p = _pts(r) x0 = min(q[0] for q in p) y0 = min(q[1] for q in p) bh = max(q[1] for q in p) - y0 d.text((x0 + 1, y0), r["text"][:60], fill=_col(i), font=_font(bh * 0.72)) return np.array(im) def _pretty(res): head = {k: res[k] for k in ("engine", "version", "image", "n_regions")} s = json.dumps(head, ensure_ascii=False, indent=2)[:-2] s += ',\n "text": ' + json.dumps(res["text"], ensure_ascii=False) s += ',\n "regions": [\n' s += ",\n".join(" " + json.dumps(r, ensure_ascii=False) for r in res["regions"]) s += "\n ]\n}" return s def run(image): if image is None: return None, None, None, "", "{}", "Bitte ein Bild hochladen." t0 = time.time() res = ocr.read(image) ms = (time.time() - t0) * 1000 R = res["regions"] boxes = _overlay(image, R) mask = _mask(image.shape, R) tlay = _textlayout(image.shape, R) status = f"✅ {res['n_regions']} Regionen · {ms:.0f} ms (CPU) — Output bereit fürs LLM" return boxes, mask, tlay, res["text"], _pretty(res), status HEADER = f"""
German-OCR
German-OCR GOCR
Deutsche OCR-Engine — ganzes Dokument → Text + Position (bbox)
Schnell · CPU, kein GPU · Output direkt fürs LLM
🇩🇪 Deutsch ⚡ CPU, kein GPU 📦 ~38 MB 🎯 bbox + JSON
""" FOOTER = f"""
Das KI-Büro für Ihre Dokumente
OCR · Vision · KI-Assistent · REST-API — on-prem, DSGVO (Frankfurt).
→ german-ocr.de
""" def build(): theme = gr.themes.Soft(primary_hue="blue", neutral_hue="slate") with gr.Blocks(title="German-OCR · GOCR", theme=theme) as demo: gr.HTML(HEADER) with gr.Row(): with gr.Column(scale=1): inp = gr.Image(label="Dokument", type="numpy", height=420) btn = gr.Button("🚀 Dokument erkennen", variant="primary", size="lg") status = gr.Textbox(label="Status", interactive=False) if os.path.isdir(EXAMPLES_DIR) and os.listdir(EXAMPLES_DIR): gr.Examples(examples=[os.path.join(EXAMPLES_DIR, f) for f in sorted(os.listdir(EXAMPLES_DIR))], inputs=inp, label="Beispiele") with gr.Column(scale=1): with gr.Tab("📦 Boxen"): out_boxes = gr.Image(label="Erkannte Regionen (Farbe je Box)", interactive=False, height=420) with gr.Tab("🎭 Maske"): out_mask = gr.Image(label="Detektions-Maske", interactive=False, height=420) with gr.Tab("🔤 Text-Layout"): out_tlay = gr.Image(label="Erkannte Werte an Position", interactive=False, height=420) with gr.Tab("📋 Text"): out_txt = gr.Textbox(label="Volltext (Lesereihenfolge)", lines=15) with gr.Tab("🔧 JSON"): out_json = gr.Code(label="Strukturiertes JSON — direkt fürs LLM/Backend", language="json") gr.HTML(FOOTER) btn.click(run, inputs=inp, outputs=[out_boxes, out_mask, out_tlay, out_txt, out_json, status]) return demo if __name__ == "__main__": build().launch(server_name="0.0.0.0", server_port=7860, allowed_paths=[EXAMPLES_DIR, os.path.expanduser("~/.cache")])