timothyafolami
162 lines
3.3 KiB
Plaintext
162 lines
3.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install -q pdfplumber"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"from text_extractor import TextExtractor\n",
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"from langchain_core.documents import Document"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"metadata": {},
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"outputs": [],
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"source": [
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"# creating a function to extract texts from image\n",
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"def create_image_document(image_path):\n",
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" # getting the image name from the image path\n",
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" image_name = image_path.split('/')[-1].split('.')[0]\n",
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" # setting image name as metadata\n",
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" metadata = {'filename': image_name}\n",
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" text_extractor = TextExtractor()\n",
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" text = text_extractor.read_text_from_image(image_path)\n",
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" # removing special characters and line breaks\n",
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" text = ''.join(e for e in text if e.isalnum() or e.isspace() or e == '\\n')\n",
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" doc = Document(page_content=text, metadata=metadata)\n",
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" # returning the document\n",
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" return [doc]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[Document(metadata={'filename': 'IMG_1438'}, page_content='ex a\\n\\nAccidented car before repair\\n')]\n"
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]
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}
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],
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"source": [
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"# testing the function\n",
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"image_path = 'data/IMG_1438.jpeg'\n",
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"text = create_image_document(image_path)\n",
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"print(text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'filename': 'IMG_1438'}"
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]
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},
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"execution_count": 28,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"text[0].metadata"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "smog_env",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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