diff options
Diffstat (limited to 'notebooks/03-look-at-iam-paragraphs.ipynb')
| -rw-r--r-- | notebooks/03-look-at-iam-paragraphs.ipynb | 226 |
1 files changed, 211 insertions, 15 deletions
diff --git a/notebooks/03-look-at-iam-paragraphs.ipynb b/notebooks/03-look-at-iam-paragraphs.ipynb index df92f99..4b82034 100644 --- a/notebooks/03-look-at-iam-paragraphs.ipynb +++ b/notebooks/03-look-at-iam-paragraphs.ipynb @@ -2,19 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "id": "6ce2519f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "import os\n", "os.environ['CUDA_VISIBLE_DEVICE'] = ''\n", @@ -39,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 162, "id": "726ac25b", "metadata": {}, "outputs": [], @@ -56,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "42501428", "metadata": {}, "outputs": [ @@ -64,7 +55,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2021-04-03 21:55:37.196 | INFO | text_recognizer.data.iam_paragraphs:setup:104 - Loading IAM paragraph regions and lines for None...\n" + "2021-04-08 21:48:18.431 | INFO | text_recognizer.data.iam_paragraphs:setup:106 - Loading IAM paragraph regions and lines for None...\n" ] }, { @@ -76,7 +67,7 @@ "Input dims: (1, 576, 640)\n", "Output dims: (682, 1)\n", "Train/val/test sizes: 1046, 262, 231\n", - "Train Batch x stats: (torch.Size([128, 1, 576, 640]), torch.float32, tensor(0.), tensor(0.0358), tensor(0.1021), tensor(1.))\n", + "Train Batch x stats: (torch.Size([128, 1, 576, 640]), torch.float32, tensor(0.), tensor(0.0371), tensor(0.1049), tensor(1.))\n", "Train Batch y stats: (torch.Size([128, 682]), torch.int64, tensor(1), tensor(83))\n", "Test Batch x stats: (torch.Size([128, 1, 576, 640]), torch.float32, tensor(0.), tensor(0.0284), tensor(0.0846), tensor(0.9373))\n", "Test Batch y stats: (torch.Size([128, 682]), torch.int64, tensor(1), tensor(83))\n", @@ -93,6 +84,211 @@ }, { "cell_type": "code", + "execution_count": 163, + "id": "0cf22683", + "metadata": {}, + "outputs": [], + "source": [ + "x, y = dataset.data_train[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "id": "98dd0ee6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([ 1, 33, 47, 44, 66, 51, 40, 59, 59, 44, 57, 66, 43, 54, 66, 53, 54, 59,\n", + " 66, 57, 44, 46, 40, 57, 43, 66, 59, 47, 44, 52, 58, 44, 51, 61, 44, 58,\n", + " 66, 40, 58, 66, 44, 63, 55, 44, 57, 59, 83, 40, 43, 61, 48, 58, 44, 57,\n", + " 58, 76, 66, 41, 60, 59, 66, 40, 57, 44, 66, 55, 57, 44, 55, 40, 57, 44,\n", + " 43, 66, 59, 54, 66, 58, 44, 44, 50, 66, 54, 60, 59, 66, 59, 47, 44, 83,\n", + " 40, 55, 55, 57, 54, 55, 57, 48, 40, 59, 44, 66, 58, 54, 60, 57, 42, 44,\n", + " 58, 66, 54, 45, 66, 48, 53, 45, 54, 57, 52, 40, 59, 48, 54, 53, 66, 54,\n", + " 57, 66, 40, 43, 61, 48, 42, 44, 78, 83, 33, 54, 62, 40, 57, 43, 58, 66,\n", + " 59, 47, 44, 66, 44, 53, 43, 66, 54, 45, 66, 5, 13, 9, 10, 76, 66, 26,\n", + " 57, 78, 66, 17, 40, 53, 48, 44, 51, 66, 20, 57, 40, 53, 59, 76, 83, 40,\n", + " 53, 66, 18, 52, 55, 51, 54, 64, 44, 44, 66, 31, 44, 51, 40, 59, 48, 54,\n", + " 53, 58, 66, 28, 45, 45, 48, 42, 44, 57, 66, 54, 45, 83, 31, 54, 51, 51,\n", + " 58, 77, 31, 54, 64, 42, 44, 66, 25, 59, 43, 78, 66, 40, 53, 43, 66, 40,\n", + " 66, 52, 44, 52, 41, 44, 57, 66, 54, 45, 66, 59, 47, 44, 83, 36, 54, 57,\n", + " 50, 44, 57, 58, 71, 66, 18, 43, 60, 42, 40, 59, 48, 54, 53, 40, 51, 66,\n", + " 14, 58, 58, 54, 42, 48, 40, 59, 48, 54, 53, 76, 66, 58, 60, 41, 52, 48,\n", + " 59, 59, 44, 43, 83, 59, 54, 66, 59, 47, 44, 66, 25, 54, 57, 43, 66, 29,\n", + " 57, 54, 61, 54, 58, 59, 66, 54, 45, 66, 20, 51, 40, 58, 46, 54, 62, 76,\n", + " 66, 17, 57, 78, 66, 14, 53, 43, 57, 44, 62, 83, 21, 54, 54, 43, 76, 66,\n", + " 40, 66, 42, 54, 55, 64, 66, 54, 45, 66, 47, 48, 58, 66, 57, 44, 55, 54,\n", + " 57, 59, 66, 54, 53, 66, 40, 53, 66, 44, 53, 56, 60, 48, 57, 64, 83, 47,\n", + " 44, 66, 47, 40, 43, 66, 52, 40, 43, 44, 66, 48, 53, 59, 54, 66, 59, 47,\n", + " 44, 66, 55, 57, 54, 41, 51, 44, 52, 58, 66, 59, 47, 40, 59, 66, 41, 44,\n", + " 58, 44, 59, 83, 54, 51, 43, 44, 57, 66, 62, 54, 57, 50, 44, 57, 58, 66,\n", + " 40, 53, 43, 66, 59, 47, 44, 66, 44, 45, 45, 44, 42, 59, 58, 66, 54, 45,\n", + " 66, 57, 44, 59, 48, 57, 44, 52, 44, 53, 59, 83, 21, 60, 46, 44, 53, 59,\n", + " 54, 41, 51, 44, 57, 66, 31, 54, 46, 44, 57, 2, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n", + " 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3])" + ] + }, + "execution_count": 164, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y" + ] + }, + { + "cell_type": "code", + "execution_count": 165, + "id": "45649194", + "metadata": {}, + "outputs": [], + "source": [ + "from text_recognizer.data.iam_preprocessor import Preprocessor\n", + "from pathlib import Path" + ] + }, + { + "cell_type": "code", + "execution_count": 166, + "id": "0fc13f9f", + "metadata": {}, + "outputs": [], + "source": [ + "processor = Preprocessor(\n", + " data_dir=Path(\"../data/downloaded/iam/iamdb\"),\n", + " num_features=1000,\n", + " lexicon_path=Path(\"../data/processed/iam_lines/iamdb_1kwp_lex_1000.txt\"),\n", + " tokens_path=Path(\"../data/processed/iam_lines/iamdb_1kwp_tokens_1000.txt\"),\n", + " use_words=True,\n", + " prepend_wordsep=False,\n", + " special_tokens=[\"<s>\", \"<e>\", \"<p>\", \"\\n\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 167, + "id": "d08a0259", + "metadata": {}, + "outputs": [], + "source": [ + "t = convert_y_label_to_string(y, dataset.mapping)" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "id": "a16a2cb7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"<s>The latter do not regard themselves as expert\\nadvisers, but are prepared to seek out the\\nappropriate sources of information or advice.\\nTowards the end of 1956, Mr. Daniel Grant,\\nan Employee Relations Officer of\\nRolls-Royce Ltd. and a member of the\\nWorkers' Educational Association, submitted\\nto the Lord Provost of Glasgow, Dr. Andrew\\nHood, a copy of his report on an enquiry\\nhe had made into the problems that beset\\nolder workers and the effects of retirement\\nHugentobler Roger<e>\"" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "t" + ] + }, + { + "cell_type": "code", + "execution_count": 170, + "id": "c7a33b2d", + "metadata": {}, + "outputs": [], + "source": [ + "ii = processor.to_index(t.replace(\" \", \"▁\").lower())" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "id": "4e0a22f4", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([247])" + ] + }, + "execution_count": 171, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ii.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 172, + "id": "bc1c5ffb", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([247])" + ] + }, + "execution_count": 172, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ii.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "id": "8b7b0373", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\"<s>▁the▁latter▁do▁not▁regard▁themselves▁as▁expert\\n▁advisers,▁but▁are▁prepared▁to▁seek▁out▁the\\n▁appropriate▁sources▁of▁information▁or▁advice.\\n▁towards▁the▁end▁of▁1956,▁mr.▁daniel▁grant,\\n▁an▁employee▁relations▁officer▁of\\n▁rolls-royce▁ltd.▁and▁a▁member▁of▁the\\n▁workers'▁educational▁association,▁submitted\\n▁to▁the▁lord▁provost▁of▁glasgow,▁dr.▁andrew\\n▁hood,▁a▁copy▁of▁his▁report▁on▁an▁enquiry\\n▁he▁had▁made▁into▁the▁problems▁that▁beset\\n▁older▁workers▁and▁the▁effects▁of▁retirement\\n▁hugentobler▁roger<e>\"" + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "processor.to_text(ii)" + ] + }, + { + "cell_type": "code", "execution_count": 4, "id": "e7778ae2", "metadata": { |