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donut/notepads/dataset_create.ipynb

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config edit, dataset create script, donut train config edit
2023-01-03 13:15:05 +01:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from huggingface_hub import login\n",
"from datasets import load_dataset\n",
"import os\n",
"import json\n",
"import shutil"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f0476002f8d14822a24f1376cfe29a07",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"login(os.environ.get(\"HUG_TOKKEN\"))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"df_train = pd.read_csv('../fiszki-ocr/train/in.tsv', sep='\\t', header=None, index_col=False)\n",
"files = [file[0] for file in df_train.iloc()]\n",
"df_train_out = pd.read_csv('../fiszki-ocr/train/expected.tsv', sep='\\t', header=None, index_col=False)\n",
"files_out = [file_out[0] for file_out in df_train_out.iloc()]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"whole = []\n",
"for file, out in zip(files, files_out):\n",
" whole.append({\"file_name\": file, \"ground_truth\": json.dumps({\"gt_parse\": {\"text_sequance\": out}}, ensure_ascii=False)})"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"train = whole[:85]\n",
"validation = whole[85:]"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"train_files = [file.get(\"file_name\") for file in train]\n",
"validation_files = [file.get(\"file_name\") for file in validation]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"for image in os.listdir(\"../fiszki-ocr/images\"):\n",
" if image in train_files:\n",
" shutil.copy(f\"/home/pc/work/fiszki-ocr/images/{image}\", f\"./images-split-fiszki/train/{image}\")\n",
" if image in validation_files:\n",
" shutil.copy(f\"/home/pc/work/fiszki-ocr/images/{image}\", f\"./images-split-fiszki/validation/{image}\")"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"\n",
"with open('./images-split-fiszki/train/metadata.jsonl', 'w', encoding='utf-8') as f:\n",
" for entry in train:\n",
" json.dump(entry, f, ensure_ascii=False)\n",
" f.write(\"\\n\")\n",
"with open('./images-split-fiszki/validation/metadata.jsonl', 'w', encoding='utf-8') as f:\n",
" for entry in validation:\n",
" json.dump(entry, f, ensure_ascii=False)\n",
" f.write(\"\\n\")\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
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"Resolving data files: 0%| | 0/86 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using custom data configuration images-split-fiszki-0b6e02834f7867a1\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading and preparing dataset imagefolder/images-split-fiszki to /home/pc/.cache/huggingface/datasets/imagefolder/images-split-fiszki-0b6e02834f7867a1/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f...\n",
" "
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"text/plain": [
"Generating train split: 0 examples [00:00, ? examples/s]"
]
},
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"Generating validation split: 0 examples [00:00, ? examples/s]"
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{
"name": "stdout",
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"text": [
"Dataset imagefolder downloaded and prepared to /home/pc/.cache/huggingface/datasets/imagefolder/images-split-fiszki-0b6e02834f7867a1/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f. Subsequent calls will reuse this data.\n"
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],
"source": [
"dataset = load_dataset('./images-split-fiszki')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Pushing split train to the Hub.\n"
]
},
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"Pushing split validation to the Hub.\n"
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],
"source": [
"dataset.push_to_hub(\"Zombely/fiszki-ocr-train\")"
]
}
],
"metadata": {
"kernelspec": {
naming change
2023-01-10 18:24:44 +01:00
"display_name": "donut",
config edit, dataset create script, donut train config edit
2023-01-03 13:15:05 +01:00
"language": "python",
"name": "python3"
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
naming change
2023-01-10 18:24:44 +01:00
"version": "3.10.8 | packaged by conda-forge | (main, Nov 24 2022, 14:07:00) [MSC v.1916 64 bit (AMD64)]"
config edit, dataset create script, donut train config edit
2023-01-03 13:15:05 +01:00
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
naming change
2023-01-10 18:24:44 +01:00
"hash": "5f15394fbb90e53eb87c79cee123a308177758b46ab7bd2ba3c7b07360ea775a"
config edit, dataset create script, donut train config edit
2023-01-03 13:15:05 +01:00
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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