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Hyper param serach results

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Sergio Jimenez Jimenez
2025-12-07 20:07:59 +01:00
parent 83522273b9
commit 09ec70de27
7 changed files with 1897 additions and 1868 deletions
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.gitignore vendored
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~$*.docx ~$*.docx
results/ results/
__pycache__/* __pycache__/
dataset dataset
results results

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prepare_dataset.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 108,
"id": "93809ffc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"%pip install --upgrade pip\n",
"%pip install --upgrade jupyter\n",
"%pip install --upgrade ipywidgets\n",
"%pip install --upgrade ipykernel"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "48724594",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: pdf2image in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (1.17.0)\n",
"Requirement already satisfied: pillow in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (12.0.0)\n",
"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: PyMuPDF in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (1.26.6)\n",
"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: pandas in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (2.3.3)\n",
"Requirement already satisfied: numpy>=1.23.2 in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from pandas) (2.3.5)\n",
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"Requirement already satisfied: six>=1.5 in c:\\users\\sergio\\appdata\\roaming\\python\\python311\\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n",
"Note: you may need to restart the kernel to use updated packages.\n",
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"Requirement already satisfied: pillow>=8 in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from matplotlib) (12.0.0)\n",
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"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: seaborn in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (0.13.2)\n",
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"Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.3.3)\n",
"Requirement already satisfied: cycler>=0.10 in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
"Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\sergio\\appdata\\local\\programs\\python\\python311\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (4.61.0)\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"# Install necessary packages\n",
"%pip install pdf2image pillow \n",
"# pdf reading\n",
"%pip install PyMuPDF\n",
"\n",
"# Data analysis and visualization\n",
"%pip install pandas\n",
"%pip install matplotlib\n",
"%pip install seaborn"
]
},
{
"cell_type": "code",
"execution_count": 110,
"id": "e1f793b6",
"metadata": {},
"outputs": [],
"source": [
"import os, json\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from pdf2image import convert_from_path\n",
"from PIL import Image, ImageOps\n",
"import fitz # PyMuPDF\n",
"import re\n",
"from datetime import datetime\n",
"from typing import List\n",
"import shutil"
]
},
{
"cell_type": "code",
"execution_count": 111,
"id": "1652a78e",
"metadata": {},
"outputs": [],
"source": [
"def pdf_to_images(pdf_path: str, output_dir: str, dpi: int = 300):\n",
" \"\"\"\n",
" Render a PDF into a list of PIL Images using PyMuPDF or pdf2image.\n",
" 'pages' is 1-based (e.g., range(1, 10) -> pages 1–9).\n",
" \"\"\"\n",
" if fitz is not None:\n",
" doc = fitz.open(pdf_path)\n",
" total_pages = len(doc)\n",
"\n",
" # Adjust page indices (PyMuPDF uses 0-based indexing)\n",
" page_indices = list(range(total_pages))\n",
"\n",
" for i in page_indices:\n",
" page = doc.load_page(i)\n",
" mat = fitz.Matrix(dpi / 72.0, dpi / 72.0)\n",
" pix = page.get_pixmap(matrix=mat, alpha=False)\n",
" img = Image.frombytes(\"RGB\", [pix.width, pix.height], pix.samples)\n",
" # Build filename\n",
" out_path = os.path.join(\n",
" output_dir,\n",
" f\"page_{i + 1:04d}.png\"\n",
" )\n",
"\n",
" img.save(out_path, \"PNG\")\n",
" doc.close()\n",
" else:\n",
" raise RuntimeError(\"Install PyMuPDF or pdf2image to convert PDFs.\")"
]
},
{
"cell_type": "code",
"execution_count": 112,
"id": "f523dd58",
"metadata": {},
"outputs": [],
"source": [
"import fitz\n",
"import re\n",
"import os\n",
"\n",
"def _pdf_extract_text_structured(page, margin_threshold=50):\n",
" \"\"\"\n",
" Extract text using PyMuPDF's dict mode which preserves\n",
" the actual line structure from the PDF.\n",
" \"\"\"\n",
" data = page.get_text(\"dict\")\n",
" \n",
" # Collect all lines with their Y position\n",
" all_lines = []\n",
" margin_text_parts = [] # Collect vertical/margin text\n",
" margin_y_positions = []\n",
" \n",
" for block in data.get(\"blocks\", []):\n",
" if block.get(\"type\") != 0: # Skip non-text blocks\n",
" continue\n",
" \n",
" block_bbox = block.get(\"bbox\", (0, 0, 0, 0))\n",
" block_width = block_bbox[2] - block_bbox[0]\n",
" block_height = block_bbox[3] - block_bbox[1]\n",
" \n",
" # Detect vertical/margin text\n",
" is_margin_text = (block_bbox[0] < margin_threshold or \n",
" block_height > block_width * 2)\n",
" \n",
" for line in block.get(\"lines\", []):\n",
" direction = line.get(\"dir\", (1, 0))\n",
" bbox = line.get(\"bbox\", (0, 0, 0, 0))\n",
" y_center = (bbox[1] + bbox[3]) / 2\n",
" x_start = bbox[0]\n",
" \n",
" # Collect text from all spans\n",
" line_text = \"\"\n",
" for span in line.get(\"spans\", []):\n",
" text = span.get(\"text\", \"\")\n",
" line_text += text\n",
" \n",
" line_text = line_text.strip()\n",
" line_text = re.sub(r\"[•▪◦●❖▶■\\uf000-\\uf0ff]\", \"\", line_text)\n",
" \n",
" if not line_text:\n",
" continue\n",
" \n",
" # Check if this is margin/vertical text\n",
" if is_margin_text or abs(direction[0]) < 0.9:\n",
" margin_text_parts.append((y_center, line_text))\n",
" margin_y_positions.append(y_center)\n",
" else:\n",
" all_lines.append((y_center, x_start, line_text))\n",
" \n",
" # Reconstruct margin text as single line at its vertical center\n",
" if margin_text_parts:\n",
" # Sort by Y position (top to bottom) and join\n",
" margin_text_parts.sort(key=lambda x: x[0])\n",
" full_margin_text = \" \".join(part[1] for part in margin_text_parts)\n",
" # Calculate vertical center of the watermark\n",
" avg_y = sum(margin_y_positions) / len(margin_y_positions)\n",
" # Add as a single line\n",
" all_lines.append((avg_y, -1, full_margin_text)) # x=-1 to sort first\n",
" \n",
" if not all_lines:\n",
" return \"\"\n",
" \n",
" # Sort by Y first, then by X\n",
" all_lines.sort(key=lambda x: (x[0], x[1]))\n",
" \n",
" # Group lines at same vertical position\n",
" merged_rows = []\n",
" current_row = [all_lines[0]]\n",
" current_y = all_lines[0][0]\n",
" \n",
" for y_center, x_start, text in all_lines[1:]:\n",
" if abs(y_center - current_y) <= 2:\n",
" current_row.append((y_center, x_start, text))\n",
" else:\n",
" current_row.sort(key=lambda x: x[1])\n",
" row_text = \" \".join(item[2] for item in current_row)\n",
" merged_rows.append((current_y, row_text))\n",
" current_row = [(y_center, x_start, text)]\n",
" current_y = y_center\n",
" \n",
" if current_row:\n",
" current_row.sort(key=lambda x: x[1])\n",
" row_text = \" \".join(item[2] for item in current_row)\n",
" merged_rows.append((current_y, row_text))\n",
" \n",
" # Sort rows by Y and extract text\n",
" merged_rows.sort(key=lambda x: x[0])\n",
" lines = [row[1] for row in merged_rows]\n",
" \n",
" # Join and clean up\n",
" text = \"\\n\".join(lines)\n",
" text = re.sub(r\" +\", \" \", text).strip()\n",
" text = re.sub(r\"\\n{3,}\", \"\\n\\n\", text).strip()\n",
" \n",
" return text\n",
"\n",
"def pdf_extract_text(pdf_path, output_dir, margin_threshold=50):\n",
" os.makedirs(output_dir, exist_ok=True)\n",
" doc = fitz.open(pdf_path)\n",
" \n",
" for i, page in enumerate(doc):\n",
" text = _pdf_extract_text_structured(page, margin_threshold)\n",
" if not text.strip():\n",
" continue\n",
" out_path = os.path.join(output_dir, f\"page_{i + 1:04d}.txt\")\n",
" with open(out_path, \"w\", encoding=\"utf-8\") as f:\n",
" f.write(text)"
]
},
{
"cell_type": "code",
"execution_count": 113,
"id": "9f64a8c0",
"metadata": {},
"outputs": [],
"source": [
"PDF_FOLDER = './instructions' # Folder containing PDF files\n",
"OUTPUT_FOLDER = './dataset'\n",
"\n",
"os.makedirs(OUTPUT_FOLDER, exist_ok=True)"
]
},
{
"cell_type": "code",
"execution_count": 114,
"id": "41e4651d",
"metadata": {},
"outputs": [],
"source": [
"i = 0\n",
"\n",
"pdf_files = sorted([\n",
" fname for fname in os.listdir(PDF_FOLDER)\n",
" if fname.lower().endswith(\".pdf\")\n",
"])\n",
"\n",
"\n",
"for fname in pdf_files:\n",
" # build output directories\n",
" out_img_path = os.path.join(OUTPUT_FOLDER, str(i), \"img\")\n",
" out_txt_path = os.path.join(OUTPUT_FOLDER, str(i), \"txt\")\n",
"\n",
" os.makedirs(out_img_path, exist_ok=True)\n",
" os.makedirs(out_txt_path, exist_ok=True)\n",
"\n",
" # source and destination PDF paths\n",
" src_pdf = os.path.join(PDF_FOLDER, fname)\n",
" pdf_path = os.path.join(OUTPUT_FOLDER, str(i), fname)\n",
"\n",
" # copy PDF into numbered folder\n",
" shutil.copy(src_pdf, pdf_path)\n",
"\n",
" # convert PDF → images\n",
" pdf_to_images(\n",
" pdf_path=pdf_path,\n",
" output_dir=out_img_path,\n",
" dpi=300\n",
" )\n",
" pdf_extract_text(\n",
" pdf_path=pdf_path,\n",
" output_dir=out_txt_path,\n",
" margin_threshold=40\n",
" )\n",
"\n",
" i += 1"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

0
dataset_manager.py → src/dataset_manager.py
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2671
paddle_ocr_fine_tune_unir_raytune.ipynb → src/paddle_ocr_fine_tune_unir_raytune.ipynb
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File diff suppressed because one or more lines are too long

25
paddle_ocr_tuning.py → src/paddle_ocr_tuning.py
View File

@@ -112,13 +112,23 @@ def assemble_from_paddle_result(paddleocr_predict, min_score=0.0, line_tol_facto
def main(): def main():
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
# dataset root folder
parser.add_argument("--pdf-folder", required=True) parser.add_argument("--pdf-folder", required=True)
#Whether to use document image orientation classification.
parser.add_argument("--use-doc-orientation-classify", type=lambda s: s.lower()=="true", default=False)
# Whether to use text image unwarping.
parser.add_argument("--use-doc-unwarping", type=lambda s: s.lower()=="true", default=False)
# Whether to use text line orientation classification.
parser.add_argument("--textline-orientation", type=lambda s: s.lower()=="true", default=True) parser.add_argument("--textline-orientation", type=lambda s: s.lower()=="true", default=True)
parser.add_argument("--text-det-box-thresh", type=float, default=0.6) # Detection pixel threshold for the text detection model. Pixels with scores greater than this threshold in the output probability map are considered text pixels.
parser.add_argument("--text-det-thresh", type=float, default=0.0)
# Detection box threshold for the text detection model. A detection result is considered a text region if the average score of all pixels within the border of the result is greater than this threshold.
parser.add_argument("--text-det-box-thresh", type=float, default=0.0)
# Text detection expansion coefficient, which expands the text region using this method. The larger the value, the larger the expansion area.
parser.add_argument("--text-det-unclip-ratio", type=float, default=1.5) parser.add_argument("--text-det-unclip-ratio", type=float, default=1.5)
# Text recognition threshold. Text results with scores greater than this threshold are retained.
parser.add_argument("--text-rec-score-thresh", type=float, default=0.0) parser.add_argument("--text-rec-score-thresh", type=float, default=0.0)
parser.add_argument("--line-tolerance", type=float, default=0.6) # text location
parser.add_argument("--min-box-score", type=float, default=0.0)
parser.add_argument("--lang", default="es") parser.add_argument("--lang", default="es")
args = parser.parse_args() args = parser.parse_args()
@@ -140,12 +150,15 @@ def main():
tp0 = time.time() tp0 = time.time()
out = ocr.predict( out = ocr.predict(
arr, arr,
use_doc_orientation_classify=args.use_doc_orientation_classify,
use_doc_unwarping=args.use_doc_unwarping,
use_textline_orientation=args.textline_orientation, #str2bool Whether to use text line orientation classification.
text_det_thresh=args.text_det_thresh,
text_det_box_thresh=args.text_det_box_thresh, text_det_box_thresh=args.text_det_box_thresh,
text_det_unclip_ratio=args.text_det_unclip_ratio, text_det_unclip_ratio=args.text_det_unclip_ratio,
text_rec_score_thresh=args.text_rec_score_thresh, text_rec_score_thresh=args.text_rec_score_thresh
use_textline_orientation=args.textline_orientation
) )
pred = assemble_from_paddle_result(out, args.min_box_score, args.line_tolerance) pred = assemble_from_paddle_result(out)
time_per_page_list.append(float(time.time() - tp0)) time_per_page_list.append(float(time.time() - tp0))
m = evaluate_text(ref, pred) m = evaluate_text(ref, pred)
cer_list.append(m["CER"]) cer_list.append(m["CER"])

504
src/prepare_dataset.ipynb Normal file
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@@ -0,0 +1,504 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "93809ffc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"%pip install --upgrade pip\n",
"%pip install --upgrade jupyter\n",
"%pip install --upgrade ipywidgets\n",
"%pip install --upgrade ipykernel"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "48724594",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting pdf2image\n",
" Using cached pdf2image-1.17.0-py3-none-any.whl.metadata (6.2 kB)\n",
"Requirement already satisfied: pillow in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (12.0.0)\n",
"Using cached pdf2image-1.17.0-py3-none-any.whl (11 kB)\n",
"Installing collected packages: pdf2image\n",
"Successfully installed pdf2image-1.17.0\n",
"Note: you may need to restart the kernel to use updated packages.\n",
"Collecting PyMuPDF\n",
" Using cached pymupdf-1.26.6-cp310-abi3-win_amd64.whl.metadata (3.4 kB)\n",
"Using cached pymupdf-1.26.6-cp310-abi3-win_amd64.whl (18.4 MB)\n",
"Installing collected packages: PyMuPDF\n",
"Successfully installed PyMuPDF-1.26.6\n",
"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: pandas in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (2.3.3)\n",
"Requirement already satisfied: numpy>=1.23.2 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from pandas) (2.3.5)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from pandas) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from pandas) (2025.2)\n",
"Requirement already satisfied: tzdata>=2022.7 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from pandas) (2025.2)\n",
"Requirement already satisfied: six>=1.5 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n",
"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: matplotlib in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (3.10.7)\n",
"Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (1.3.3)\n",
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"Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (4.61.0)\n",
"Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (1.4.9)\n",
"Requirement already satisfied: numpy>=1.23 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (2.3.5)\n",
"Requirement already satisfied: packaging>=20.0 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (25.0)\n",
"Requirement already satisfied: pillow>=8 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (12.0.0)\n",
"Requirement already satisfied: pyparsing>=3 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib) (3.2.5)\n",
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"Note: you may need to restart the kernel to use updated packages.\n",
"Requirement already satisfied: seaborn in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (0.13.2)\n",
"Requirement already satisfied: numpy!=1.24.0,>=1.20 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from seaborn) (2.3.5)\n",
"Requirement already satisfied: pandas>=1.2 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from seaborn) (2.3.3)\n",
"Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from seaborn) (3.10.7)\n",
"Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.3.3)\n",
"Requirement already satisfied: cycler>=0.10 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
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"Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.4.9)\n",
"Requirement already satisfied: packaging>=20.0 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (25.0)\n",
"Requirement already satisfied: pillow>=8 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (12.0.0)\n",
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"Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (2.9.0.post0)\n",
"Requirement already satisfied: pytz>=2020.1 in c:\\users\\sergio\\desktop\\mastersthesis\\.venv\\lib\\site-packages (from pandas>=1.2->seaborn) (2025.2)\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"# Install necessary packages\n",
"%pip install pdf2image pillow \n",
"# pdf reading\n",
"%pip install PyMuPDF\n",
"\n",
"# Data analysis and visualization\n",
"%pip install pandas\n",
"%pip install matplotlib\n",
"%pip install seaborn"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e1f793b6",
"metadata": {},
"outputs": [],
"source": [
"import os, json\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from pdf2image import convert_from_path\n",
"from PIL import Image, ImageOps\n",
"import fitz # PyMuPDF\n",
"import re\n",
"from datetime import datetime\n",
"from typing import List\n",
"import shutil"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "1652a78e",
"metadata": {},
"outputs": [],
"source": [
"def pdf_to_images(pdf_path: str, output_dir: str, dpi: int = 300):\n",
" \"\"\"\n",
" Render a PDF into a list of PIL Images using PyMuPDF or pdf2image.\n",
" 'pages' is 1-based (e.g., range(1, 10) -> pages 1–9).\n",
" \"\"\"\n",
" if fitz is not None:\n",
" doc = fitz.open(pdf_path)\n",
" total_pages = len(doc)\n",
"\n",
" # Adjust page indices (PyMuPDF uses 0-based indexing)\n",
" page_indices = list(range(total_pages))\n",
"\n",
" for i in page_indices:\n",
" page = doc.load_page(i)\n",
" mat = fitz.Matrix(dpi / 72.0, dpi / 72.0)\n",
" pix = page.get_pixmap(matrix=mat, alpha=False)\n",
" img = Image.frombytes(\"RGB\", [pix.width, pix.height], pix.samples)\n",
" # Build filename\n",
" out_path = os.path.join(\n",
" output_dir,\n",
" f\"page_{i + 1:04d}.png\"\n",
" )\n",
"\n",
" img.save(out_path, \"PNG\")\n",
" doc.close()\n",
" else:\n",
" raise RuntimeError(\"Install PyMuPDF or pdf2image to convert PDFs.\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "f523dd58",
"metadata": {},
"outputs": [],
"source": [
"import fitz\n",
"import re\n",
"import os\n",
"\n",
"def _pdf_extract_text_structured(page, margin_threshold=50):\n",
" \"\"\"\n",
" Extract text using PyMuPDF's dict mode which preserves\n",
" the actual line structure from the PDF.\n",
" \"\"\"\n",
" data = page.get_text(\"dict\")\n",
" \n",
" # Collect all lines with their Y position\n",
" all_lines = []\n",
" margin_text_parts = [] # Collect vertical/margin text\n",
" margin_y_positions = []\n",
" \n",
" for block in data.get(\"blocks\", []):\n",
" if block.get(\"type\") != 0: # Skip non-text blocks\n",
" continue\n",
" \n",
" block_bbox = block.get(\"bbox\", (0, 0, 0, 0))\n",
" block_width = block_bbox[2] - block_bbox[0]\n",
" block_height = block_bbox[3] - block_bbox[1]\n",
" \n",
" # Detect vertical/margin text\n",
" is_margin_text = (block_bbox[0] < margin_threshold or \n",
" block_height > block_width * 2)\n",
" \n",
" for line in block.get(\"lines\", []):\n",
" direction = line.get(\"dir\", (1, 0))\n",
" bbox = line.get(\"bbox\", (0, 0, 0, 0))\n",
" y_center = (bbox[1] + bbox[3]) / 2\n",
" x_start = bbox[0]\n",
" \n",
" # Collect text from all spans\n",
" line_text = \"\"\n",
" for span in line.get(\"spans\", []):\n",
" text = span.get(\"text\", \"\")\n",
" line_text += text\n",
" \n",
" line_text = line_text.strip()\n",
" line_text = re.sub(r\"[•▪◦●❖▶■\\uf000-\\uf0ff]\", \"\", line_text)\n",
" \n",
" if not line_text:\n",
" continue\n",
" \n",
" # Check if this is margin/vertical text\n",
" if is_margin_text or abs(direction[0]) < 0.9:\n",
" margin_text_parts.append((y_center, line_text))\n",
" margin_y_positions.append(y_center)\n",
" else:\n",
" all_lines.append((y_center, x_start, line_text))\n",
" \n",
" # Reconstruct margin text as single line at its vertical center\n",
" if margin_text_parts:\n",
" # Sort by Y position (top to bottom) and join\n",
" margin_text_parts.sort(key=lambda x: x[0])\n",
" full_margin_text = \" \".join(part[1] for part in margin_text_parts)\n",
" # Calculate vertical center of the watermark\n",
" avg_y = sum(margin_y_positions) / len(margin_y_positions)\n",
" # Add as a single line\n",
" all_lines.append((avg_y, -1, full_margin_text)) # x=-1 to sort first\n",
" \n",
" if not all_lines:\n",
" return \"\"\n",
" \n",
" # Sort by Y first, then by X\n",
" all_lines.sort(key=lambda x: (x[0], x[1]))\n",
" \n",
" # Group lines at same vertical position\n",
" merged_rows = []\n",
" current_row = [all_lines[0]]\n",
" current_y = all_lines[0][0]\n",
" \n",
" for y_center, x_start, text in all_lines[1:]:\n",
" if abs(y_center - current_y) <= 2:\n",
" current_row.append((y_center, x_start, text))\n",
" else:\n",
" current_row.sort(key=lambda x: x[1])\n",
" row_text = \" \".join(item[2] for item in current_row)\n",
" merged_rows.append((current_y, row_text))\n",
" current_row = [(y_center, x_start, text)]\n",
" current_y = y_center\n",
" \n",
" if current_row:\n",
" current_row.sort(key=lambda x: x[1])\n",
" row_text = \" \".join(item[2] for item in current_row)\n",
" merged_rows.append((current_y, row_text))\n",
" \n",
" # Sort rows by Y and extract text\n",
" merged_rows.sort(key=lambda x: x[0])\n",
" lines = [row[1] for row in merged_rows]\n",
" \n",
" # Join and clean up\n",
" text = \"\\n\".join(lines)\n",
" text = re.sub(r\" +\", \" \", text).strip()\n",
" text = re.sub(r\"\\n{3,}\", \"\\n\\n\", text).strip()\n",
" \n",
" return text\n",
"\n",
"def pdf_extract_text(pdf_path, output_dir, margin_threshold=50):\n",
" os.makedirs(output_dir, exist_ok=True)\n",
" doc = fitz.open(pdf_path)\n",
" \n",
" for i, page in enumerate(doc):\n",
" text = _pdf_extract_text_structured(page, margin_threshold)\n",
" if not text.strip():\n",
" continue\n",
" out_path = os.path.join(output_dir, f\"page_{i + 1:04d}.txt\")\n",
" with open(out_path, \"w\", encoding=\"utf-8\") as f:\n",
" f.write(text)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "9f64a8c0",
"metadata": {},
"outputs": [],
"source": [
"PDF_FOLDER = './../instructions' # Folder containing PDF files\n",
"OUTPUT_FOLDER = './dataset'\n",
"\n",
"os.makedirs(OUTPUT_FOLDER, exist_ok=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "41e4651d",
"metadata": {},
"outputs": [],
"source": [
"i = 0\n",
"\n",
"pdf_files = sorted([\n",
" fname for fname in os.listdir(PDF_FOLDER)\n",
" if fname.lower().endswith(\".pdf\")\n",
"])\n",
"\n",
"\n",
"for fname in pdf_files:\n",
" # build output directories\n",
" out_img_path = os.path.join(OUTPUT_FOLDER, str(i), \"img\")\n",
" out_txt_path = os.path.join(OUTPUT_FOLDER, str(i), \"txt\")\n",
"\n",
" os.makedirs(out_img_path, exist_ok=True)\n",
" os.makedirs(out_txt_path, exist_ok=True)\n",
"\n",
" # source and destination PDF paths\n",
" src_pdf = os.path.join(PDF_FOLDER, fname)\n",
" pdf_path = os.path.join(OUTPUT_FOLDER, str(i), fname)\n",
"\n",
" # copy PDF into numbered folder\n",
" shutil.copy(src_pdf, pdf_path)\n",
"\n",
" # convert PDF → images\n",
" pdf_to_images(\n",
" pdf_path=pdf_path,\n",
" output_dir=out_img_path,\n",
" dpi=300\n",
" )\n",
" pdf_extract_text(\n",
" pdf_path=pdf_path,\n",
" output_dir=out_txt_path,\n",
" margin_threshold=40\n",
" )\n",
"\n",
" i += 1"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv (3.11.9)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

65
src/raytune_paddle_subproc_results_20251207_192320.csv Normal file
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@@ -0,0 +1,65 @@
CER,WER,TIME,PAGES,TIME_PER_PAGE,timestamp,checkpoint_dir_name,done,training_iteration,trial_id,date,time_this_iter_s,time_total_s,pid,hostname,node_ip,time_since_restore,iterations_since_restore,config/use_doc_orientation_classify,config/use_doc_unwarping,config/textline_orientation,config/text_det_thresh,config/text_det_box_thresh,config/text_det_unclip_ratio,config/text_rec_score_thresh,logdir
0.013515850203159258,0.1050034776034098,353.85077571868896,5,70.66230463981628,1765120215,,False,1,d5238c33,2025-12-07_16-10-15,374.27777338027954,374.27777338027954,19452,LAPTOP-2OQK6GT5,127.0.0.1,374.27777338027954,1,True,False,True,0.08878208965533294,0.623029468177504,0.0,0.22994386685874743,d5238c33
0.03905195479212187,0.13208645252197226,354.61478638648987,5,70.82208666801452,1765120220,,False,1,ea8a2f7a,2025-12-07_16-10-20,374.2999520301819,374.2999520301819,7472,LAPTOP-2OQK6GT5,127.0.0.1,374.2999520301819,1,False,False,False,0.39320080607112917,0.6712014538998344,0.0,0.16880221913810864,ea8a2f7a
0.06606238373546518,0.16619192810354325,359.09717535972595,5,71.72569246292115,1765120601,,False,1,ebb12e5b,2025-12-07_16-16-41,379.5437698364258,379.5437698364258,21480,LAPTOP-2OQK6GT5,127.0.0.1,379.5437698364258,1,True,True,True,0.4328784710891528,0.23572507118228522,0.0,0.18443532434104057,ebb12e5b
0.41810946199338,0.5037103242611287,336.6613118648529,5,67.22685413360595,1765120583,,False,1,b3775034,2025-12-07_16-16-23,356.52618169784546,356.52618169784546,23084,LAPTOP-2OQK6GT5,127.0.0.1,356.52618169784546,1,True,True,False,0.06412882230680782,0.3377439247010605,0.0,0.5764053439963283,b3775034
0.1972515944870667,0.2953531713611584,350.1465151309967,5,69.93639450073242,1765120959,,False,1,bf10d370,2025-12-07_16-22-39,370.90337228775024,370.90337228775024,26140,LAPTOP-2OQK6GT5,127.0.0.1,370.90337228775024,1,True,True,True,0.6719551054359146,0.6902317374774642,0.0,0.3964896632708511,bf10d370
0.3864103728596727,0.45583610828383464,320.96620512008667,5,64.09520988464355,1765120947,,False,1,111e5a9e,2025-12-07_16-22-27,341.0712642669678,341.0712642669678,20664,LAPTOP-2OQK6GT5,127.0.0.1,341.0712642669678,1,True,False,False,0.04481600265034593,0.4832664381621284,0.0,0.5464155154391461,111e5a9e
0.5160689446919982,0.5945298276300801,326.65670347213745,5,65.2350733757019,1765121300,,False,1,415d7ba1,2025-12-07_16-28-20,347.29887080192566,347.29887080192566,23848,LAPTOP-2OQK6GT5,127.0.0.1,347.29887080192566,1,True,True,True,0.01699705273201909,0.5233849789194689,0.0,0.20833106578160068,415d7ba1
0.5025130639131208,0.5677161936883898,326.9156484603882,5,65.28343558311462,1765121310,,False,1,a58d8109,2025-12-07_16-28-30,346.09022212028503,346.09022212028503,25248,LAPTOP-2OQK6GT5,127.0.0.1,346.09022212028503,1,False,True,True,0.04024319071476844,0.6705892008057031,0.0,0.1885847677314521,a58d8109
0.07092029393242118,0.17390976502682037,368.5711796283722,5,73.62503981590271,1765121692,,False,1,33bdf2a9,2025-12-07_16-34-52,388.150607585907,388.150607585907,24024,LAPTOP-2OQK6GT5,127.0.0.1,388.150607585907,1,False,True,False,0.4347371576992484,0.490009080993297,0.0,0.1519055407457635,33bdf2a9
0.1168252568583151,0.22212978798067146,364.6228621006012,5,72.82479510307311,1765121699,,False,1,d9df79f3,2025-12-07_16-34-59,384.67676973342896,384.67676973342896,5368,LAPTOP-2OQK6GT5,127.0.0.1,384.67676973342896,1,True,True,False,0.17806350429159667,0.6261942434824851,0.0,0.38547742746319813,d9df79f3
0.06459478599489028,0.16493742503085831,366.6067085266113,5,73.22199411392212,1765122086,,False,1,80ea65f2,2025-12-07_16-41-26,387.6792531013489,387.6792531013489,14064,LAPTOP-2OQK6GT5,127.0.0.1,387.6792531013489,1,True,True,False,0.6011116675422127,0.25138233186284487,0.0,0.31312371671514233,80ea65f2
0.01340057642794312,0.10741926673961485,359.5969452857971,5,71.80434017181396,1765122084,,False,1,2e978bfa,2025-12-07_16-41-24,380.28105759620667,380.28105759620667,11060,LAPTOP-2OQK6GT5,127.0.0.1,380.28105759620667,1,False,False,True,0.23485911670668447,0.07773192307960775,0.0,0.023694797982285992,2e978bfa
0.01340057642794312,0.10741926673961485,347.92934703826904,5,69.49003491401672,1765122459,,False,1,8518cc40,2025-12-07_16-47-39,368.54625153541565,368.54625153541565,21016,LAPTOP-2OQK6GT5,127.0.0.1,368.54625153541565,1,False,False,True,0.2225556801158737,0.00024186765038358704,0.0,0.0028910785387807336,8518cc40
0.01340057642794312,0.10741926673961485,347.14498376846313,5,69.324178647995,1765122461,,False,1,2c691aaa,2025-12-07_16-47-41,366.3459825515747,366.3459825515747,21540,LAPTOP-2OQK6GT5,127.0.0.1,366.3459825515747,1,False,False,True,0.22472742766369874,0.030333356491349384,0.0,0.05099688981312009,2c691aaa
0.013040374955575204,0.10485434443992256,347.22006940841675,5,69.34554209709168,1765122832,,False,1,31e60691,2025-12-07_16-53-52,368.0382122993469,368.0382122993469,17532,LAPTOP-2OQK6GT5,127.0.0.1,368.0382122993469,1,False,False,True,0.25914070057597594,0.0019604082489898533,0.0,0.0035094431353713818,31e60691
0.012582941415352794,0.10327954129031627,349.2319846153259,5,69.74626359939575,1765122837,,False,1,d4d288c6,2025-12-07_16-53-57,368.903502702713,368.903502702713,22216,LAPTOP-2OQK6GT5,127.0.0.1,368.903502702713,1,False,False,True,0.2734075225731028,0.0033989235904911125,0.0,0.015420451500634869,d4d288c6
0.012582941415352794,0.10327954129031627,346.6979134082794,5,69.24065437316895,1765123205,,False,1,7645b77c,2025-12-07_17-00-05,367.4564206600189,367.4564206600189,2272,LAPTOP-2OQK6GT5,127.0.0.1,367.4564206600189,1,False,False,True,0.279241869770728,0.1138413707810162,0.0,0.07531508117874008,7645b77c
0.012407575745987933,0.10201566081383735,346.5196530818939,5,69.19977960586547,1765123208,,False,1,3256ae36,2025-12-07_17-00-08,366.00227642059326,366.00227642059326,6604,LAPTOP-2OQK6GT5,127.0.0.1,366.00227642059326,1,False,False,True,0.30993017979826853,0.1292131176570399,0.0,0.11201957956206357,3256ae36
0.012407575745987933,0.10201566081383735,344.0291979312897,5,68.71350336074829,1765123575,,False,1,b0dda58b,2025-12-07_17-06-15,364.82790350914,364.82790350914,9732,LAPTOP-2OQK6GT5,127.0.0.1,364.82790350914,1,False,False,True,0.3149521989502957,0.11783753596277924,0.0,0.6825729339913746,b0dda58b
0.012429753445092291,0.10205118268939237,346.11818265914917,5,69.12530856132507,1765123581,,False,1,e9d40333,2025-12-07_17-06-21,365.62638425827026,365.62638425827026,23416,LAPTOP-2OQK6GT5,127.0.0.1,365.62638425827026,1,False,False,True,0.5302520310849914,0.1569390945373281,0.0,0.10019443545563994,e9d40333
0.011990675508758594,0.10047637953978608,346.5398359298706,5,69.2183114528656,1765123948,,False,1,aa89fe7a,2025-12-07_17-12-28,366.7530257701874,366.7530257701874,16200,LAPTOP-2OQK6GT5,127.0.0.1,366.7530257701874,1,False,False,True,0.5039700850900125,0.16208277029791282,0.0,0.6765386284546205,aa89fe7a
0.011968497809654236,0.10044085766423105,345.97880601882935,5,69.09321279525757,1765123951,,False,1,92c48d07,2025-12-07_17-12-31,365.0942301750183,365.0942301750183,15432,LAPTOP-2OQK6GT5,127.0.0.1,365.0942301750183,1,False,False,True,0.33321916406589397,0.1864428656555301,0.0,0.6775297319325386,92c48d07
0.011968497809654236,0.10044085766423105,344.1725525856018,5,68.74226913452148,1765124318,,False,1,187790d7,2025-12-07_17-18-38,364.47401189804077,364.47401189804077,24676,LAPTOP-2OQK6GT5,127.0.0.1,364.47401189804077,1,False,False,True,0.3372505528404193,0.2352515935896671,0.0,0.6987321324340134,187790d7
0.011760127958326316,0.09964993325879434,345.9427492618561,5,69.08389501571655,1765124322,,False,1,442a2439,2025-12-07_17-18-42,364.755074262619,364.755074262619,7892,LAPTOP-2OQK6GT5,127.0.0.1,364.755074262619,1,False,False,True,0.5098036701758629,0.2122757290966333,0.0,0.6992468303721803,442a2439
0.011968497809654236,0.10044085766423105,345.40264558792114,5,68.98561010360717,1765124689,,False,1,70862adc,2025-12-07_17-24-49,365.9752175807953,365.9752175807953,15412,LAPTOP-2OQK6GT5,127.0.0.1,365.9752175807953,1,False,False,True,0.3963969237347287,0.2163058925653838,0.0,0.6859176720785957,70862adc
0.012407575745987933,0.10201566081383735,345.8808228969574,5,69.07736506462098,1765124693,,False,1,e6821f34,2025-12-07_17-24-53,365.25493717193604,365.25493717193604,26088,LAPTOP-2OQK6GT5,127.0.0.1,365.25493717193604,1,False,False,True,0.3668982772069688,0.2407751620351906,0.0,0.5737620270733486,e6821f34
0.012199205894660016,0.10122473640840064,347.05629682540894,5,69.31870231628417,1765125062,,False,1,8b680875,2025-12-07_17-31-02,367.2029130458832,367.2029130458832,1720,LAPTOP-2OQK6GT5,127.0.0.1,367.2029130458832,1,False,False,True,0.5312495877753942,0.3193426688929859,0.0,0.591252589724218,8b680875
0.012429753445092291,0.10205118268939237,349.60691928863525,5,69.8253363609314,1765125068,,False,1,fc54867b,2025-12-07_17-31-08,368.73608803749084,368.73608803749084,4888,LAPTOP-2OQK6GT5,127.0.0.1,368.73608803749084,1,False,False,True,0.5034080657304706,0.3042864908472832,0.0,0.5024906014323391,fc54867b
0.013385453418768206,0.10927323740570172,343.8553657531738,5,68.67559289932251,1765125432,,False,1,c32d0d5e,2025-12-07_17-37-12,364.42339730262756,364.42339730262756,25808,LAPTOP-2OQK6GT5,127.0.0.1,364.42339730262756,1,False,False,True,0.15300672154002157,0.39848899797721926,0.0,0.5167681121564286,c32d0d5e
0.013537204772521452,0.10852488053708713,344.60119009017944,5,68.81447420120239,1765125436,,False,1,4762fbbb,2025-12-07_17-37-16,363.3258783817291,363.3258783817291,20760,LAPTOP-2OQK6GT5,127.0.0.1,363.3258783817291,1,False,False,True,0.13342603167575784,0.4010104919178914,0.0,0.618812411626611,4762fbbb
0.011763789518968464,0.09968897796498292,344.03784108161926,5,68.71829047203065,1765125803,,False,1,522ac97c,2025-12-07_17-43-23,364.7200028896332,364.7200028896332,2372,LAPTOP-2OQK6GT5,127.0.0.1,364.7200028896332,1,False,False,True,0.4489762005319642,0.402754966715804,0.0,0.6426372526242771,522ac97c
0.011650346524073398,0.09890157639017978,343.51321721076965,5,68.60030875205993,1765125805,,False,1,5784f433,2025-12-07_17-43-25,362.93026328086853,362.93026328086853,22900,LAPTOP-2OQK6GT5,127.0.0.1,362.93026328086853,1,False,False,True,0.46204975067512033,0.192768833446102,0.0,0.6328281433384326,5784f433
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0.01153507274885726,0.09890157639017978,345.8425042629242,5,69.06782102584839,1765130290,,False,1,076c5450,2025-12-07_18-58-10,365.1877450942993,365.1877450942993,4832,LAPTOP-2OQK6GT5,127.0.0.1,365.1877450942993,1,False,False,True,0.48842171509426413,0.5881329256041945,0.0,0.6569193185887352,076c5450
0.011875401733542455,0.10047637953978608,350.2443346977234,5,69.94839100837707,1765130664,,False,1,4a42a3ea,2025-12-07_19-04-24,370.9968421459198,370.9968421459198,14912,LAPTOP-2OQK6GT5,127.0.0.1,370.9968421459198,1,False,False,True,0.5590357657789103,0.5940413385819063,0.0,0.6573225721220606,4a42a3ea
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0.012314479669876154,0.10205118268939237,343.53907656669617,5,68.6134319782257,1765131035,,False,1,8abb3f37,2025-12-07_19-10-35,364.67463064193726,364.67463064193726,22012,LAPTOP-2OQK6GT5,127.0.0.1,364.67463064193726,1,False,False,True,0.48982107744168,0.4636820835063238,0.0,0.39458266779240964,8abb3f37
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0.011875401733542455,0.10047637953978608,355.52406072616577,5,71.00808920860291,1765131794,,False,1,33ea1cc6,2025-12-07_19-23-14,376.746440410614,376.746440410614,17380,LAPTOP-2OQK6GT5,127.0.0.1,376.746440410614,1,False,False,True,0.5229924883346121,0.5158065672775711,0.0,0.6679657240993034,33ea1cc6
0.011853224034438097,0.10044085766423105,355.67893862724304,5,71.0243070602417,1765131797,,False,1,1243723e,2025-12-07_19-23-17,375.44413685798645,375.44413685798645,11232,LAPTOP-2OQK6GT5,127.0.0.1,375.44413685798645,1,False,False,True,0.3726772055073363,0.5573152713604742,0.0,0.6766134238094554,1243723e
1 CER WER TIME PAGES TIME_PER_PAGE timestamp checkpoint_dir_name done training_iteration trial_id date time_this_iter_s time_total_s pid hostname node_ip time_since_restore iterations_since_restore config/use_doc_orientation_classify config/use_doc_unwarping config/textline_orientation config/text_det_thresh config/text_det_box_thresh config/text_det_unclip_ratio config/text_rec_score_thresh logdir
2 0.013515850203159258 0.1050034776034098 353.85077571868896 5 70.66230463981628 1765120215 False 1 d5238c33 2025-12-07_16-10-15 374.27777338027954 374.27777338027954 19452 LAPTOP-2OQK6GT5 127.0.0.1 374.27777338027954 1 True False True 0.08878208965533294 0.623029468177504 0.0 0.22994386685874743 d5238c33
3 0.03905195479212187 0.13208645252197226 354.61478638648987 5 70.82208666801452 1765120220 False 1 ea8a2f7a 2025-12-07_16-10-20 374.2999520301819 374.2999520301819 7472 LAPTOP-2OQK6GT5 127.0.0.1 374.2999520301819 1 False False False 0.39320080607112917 0.6712014538998344 0.0 0.16880221913810864 ea8a2f7a
4 0.06606238373546518 0.16619192810354325 359.09717535972595 5 71.72569246292115 1765120601 False 1 ebb12e5b 2025-12-07_16-16-41 379.5437698364258 379.5437698364258 21480 LAPTOP-2OQK6GT5 127.0.0.1 379.5437698364258 1 True True True 0.4328784710891528 0.23572507118228522 0.0 0.18443532434104057 ebb12e5b
5 0.41810946199338 0.5037103242611287 336.6613118648529 5 67.22685413360595 1765120583 False 1 b3775034 2025-12-07_16-16-23 356.52618169784546 356.52618169784546 23084 LAPTOP-2OQK6GT5 127.0.0.1 356.52618169784546 1 True True False 0.06412882230680782 0.3377439247010605 0.0 0.5764053439963283 b3775034
6 0.1972515944870667 0.2953531713611584 350.1465151309967 5 69.93639450073242 1765120959 False 1 bf10d370 2025-12-07_16-22-39 370.90337228775024 370.90337228775024 26140 LAPTOP-2OQK6GT5 127.0.0.1 370.90337228775024 1 True True True 0.6719551054359146 0.6902317374774642 0.0 0.3964896632708511 bf10d370
7 0.3864103728596727 0.45583610828383464 320.96620512008667 5 64.09520988464355 1765120947 False 1 111e5a9e 2025-12-07_16-22-27 341.0712642669678 341.0712642669678 20664 LAPTOP-2OQK6GT5 127.0.0.1 341.0712642669678 1 True False False 0.04481600265034593 0.4832664381621284 0.0 0.5464155154391461 111e5a9e
8 0.5160689446919982 0.5945298276300801 326.65670347213745 5 65.2350733757019 1765121300 False 1 415d7ba1 2025-12-07_16-28-20 347.29887080192566 347.29887080192566 23848 LAPTOP-2OQK6GT5 127.0.0.1 347.29887080192566 1 True True True 0.01699705273201909 0.5233849789194689 0.0 0.20833106578160068 415d7ba1
9 0.5025130639131208 0.5677161936883898 326.9156484603882 5 65.28343558311462 1765121310 False 1 a58d8109 2025-12-07_16-28-30 346.09022212028503 346.09022212028503 25248 LAPTOP-2OQK6GT5 127.0.0.1 346.09022212028503 1 False True True 0.04024319071476844 0.6705892008057031 0.0 0.1885847677314521 a58d8109
10 0.07092029393242118 0.17390976502682037 368.5711796283722 5 73.62503981590271 1765121692 False 1 33bdf2a9 2025-12-07_16-34-52 388.150607585907 388.150607585907 24024 LAPTOP-2OQK6GT5 127.0.0.1 388.150607585907 1 False True False 0.4347371576992484 0.490009080993297 0.0 0.1519055407457635 33bdf2a9
11 0.1168252568583151 0.22212978798067146 364.6228621006012 5 72.82479510307311 1765121699 False 1 d9df79f3 2025-12-07_16-34-59 384.67676973342896 384.67676973342896 5368 LAPTOP-2OQK6GT5 127.0.0.1 384.67676973342896 1 True True False 0.17806350429159667 0.6261942434824851 0.0 0.38547742746319813 d9df79f3
12 0.06459478599489028 0.16493742503085831 366.6067085266113 5 73.22199411392212 1765122086 False 1 80ea65f2 2025-12-07_16-41-26 387.6792531013489 387.6792531013489 14064 LAPTOP-2OQK6GT5 127.0.0.1 387.6792531013489 1 True True False 0.6011116675422127 0.25138233186284487 0.0 0.31312371671514233 80ea65f2
13 0.01340057642794312 0.10741926673961485 359.5969452857971 5 71.80434017181396 1765122084 False 1 2e978bfa 2025-12-07_16-41-24 380.28105759620667 380.28105759620667 11060 LAPTOP-2OQK6GT5 127.0.0.1 380.28105759620667 1 False False True 0.23485911670668447 0.07773192307960775 0.0 0.023694797982285992 2e978bfa
14 0.01340057642794312 0.10741926673961485 347.92934703826904 5 69.49003491401672 1765122459 False 1 8518cc40 2025-12-07_16-47-39 368.54625153541565 368.54625153541565 21016 LAPTOP-2OQK6GT5 127.0.0.1 368.54625153541565 1 False False True 0.2225556801158737 0.00024186765038358704 0.0 0.0028910785387807336 8518cc40
15 0.01340057642794312 0.10741926673961485 347.14498376846313 5 69.324178647995 1765122461 False 1 2c691aaa 2025-12-07_16-47-41 366.3459825515747 366.3459825515747 21540 LAPTOP-2OQK6GT5 127.0.0.1 366.3459825515747 1 False False True 0.22472742766369874 0.030333356491349384 0.0 0.05099688981312009 2c691aaa
16 0.013040374955575204 0.10485434443992256 347.22006940841675 5 69.34554209709168 1765122832 False 1 31e60691 2025-12-07_16-53-52 368.0382122993469 368.0382122993469 17532 LAPTOP-2OQK6GT5 127.0.0.1 368.0382122993469 1 False False True 0.25914070057597594 0.0019604082489898533 0.0 0.0035094431353713818 31e60691
17 0.012582941415352794 0.10327954129031627 349.2319846153259 5 69.74626359939575 1765122837 False 1 d4d288c6 2025-12-07_16-53-57 368.903502702713 368.903502702713 22216 LAPTOP-2OQK6GT5 127.0.0.1 368.903502702713 1 False False True 0.2734075225731028 0.0033989235904911125 0.0 0.015420451500634869 d4d288c6
18 0.012582941415352794 0.10327954129031627 346.6979134082794 5 69.24065437316895 1765123205 False 1 7645b77c 2025-12-07_17-00-05 367.4564206600189 367.4564206600189 2272 LAPTOP-2OQK6GT5 127.0.0.1 367.4564206600189 1 False False True 0.279241869770728 0.1138413707810162 0.0 0.07531508117874008 7645b77c
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