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+ {
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+ "nbformat": 4,
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+ "nbformat_minor": 0,
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+ "metadata": {
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+ "colab": {
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+ "provenance": []
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+ },
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+ "kernelspec": {
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+ "name": "python3",
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+ "display_name": "Python 3"
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+ },
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+ "language_info": {
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+ "name": "python"
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+ }
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+ },
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "!pip install openai==0.28"
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+ ],
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "ROE6pVjqkT-L",
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+ "outputId": "01c9f4da-81a9-43ed-c3ac-572e96880a2b"
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+ },
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+ "execution_count": 1,
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "Collecting openai==0.28\n",
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+ " Downloading openai-0.28.0-py3-none-any.whl.metadata (13 kB)\n",
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+ "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.11/dist-packages (from openai==0.28) (2.32.3)\n",
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+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.20->openai==0.28) (3.4.1)\n",
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+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.20->openai==0.28) (3.10)\n",
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+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.20->openai==0.28) (2.3.0)\n",
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+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.20->openai==0.28) (2024.12.14)\n",
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+ "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->openai==0.28) (1.18.3)\n",
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+ "Downloading openai-0.28.0-py3-none-any.whl (76 kB)\n",
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+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.5/76.5 kB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+ "\u001b[?25hInstalling collected packages: openai\n",
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+ " Attempting uninstall: openai\n",
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+ " Found existing installation: openai 1.59.9\n",
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+ " Uninstalling openai-1.59.9:\n",
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+ " Successfully uninstalled openai-1.59.9\n",
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+ "Successfully installed openai-0.28.0\n"
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+ ]
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "!pip install pdf2image\n",
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+ "!sudo apt-get install poppler-utils\n"
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+ ],
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "-QwkjUM-lCOS",
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+ "outputId": "02d87d12-9026-4601-a3ad-f92ea74c3a6c"
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+ "execution_count": 2,
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "Collecting pdf2image\n",
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+ " Downloading pdf2image-1.17.0-py3-none-any.whl.metadata (6.2 kB)\n",
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+ "Requirement already satisfied: pillow in /usr/local/lib/python3.11/dist-packages (from pdf2image) (11.1.0)\n",
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+ "Downloading pdf2image-1.17.0-py3-none-any.whl (11 kB)\n",
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+ "Installing collected packages: pdf2image\n",
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+ "Successfully installed pdf2image-1.17.0\n",
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+ "Reading package lists... Done\n",
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+ "Building dependency tree... Done\n",
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+ "Reading state information... Done\n",
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+ "The following NEW packages will be installed:\n",
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+ " poppler-utils\n",
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+ "0 upgraded, 1 newly installed, 0 to remove and 18 not upgraded.\n",
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+ "Need to get 186 kB of archives.\n",
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+ "After this operation, 696 kB of additional disk space will be used.\n",
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+ "Get:1 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 poppler-utils amd64 22.02.0-2ubuntu0.6 [186 kB]\n",
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+ "Fetched 186 kB in 1s (260 kB/s)\n",
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+ "debconf: unable to initialize frontend: Dialog\n",
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+ "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 78, <> line 1.)\n",
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+ "debconf: falling back to frontend: Readline\n",
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+ "debconf: falling back to frontend: Teletype\n",
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+ "dpkg-preconfigure: unable to re-open stdin: \n",
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+ "Selecting previously unselected package poppler-utils.\n",
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+ "(Reading database ... 124950 files and directories currently installed.)\n",
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+ "Preparing to unpack .../poppler-utils_22.02.0-2ubuntu0.6_amd64.deb ...\n",
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+ "Setting up poppler-utils (22.02.0-2ubuntu0.6) ...\n",
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+ "Processing triggers for man-db (2.10.2-1) ...\n"
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+ ]
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "import openai\n",
119
+ "from pdf2image import convert_from_path\n",
120
+ "import json\n",
121
+ "import pandas as pd\n",
122
+ "import os\n",
123
+ "import base64\n",
124
+ "import re\n",
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+ "\n",
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+ "# OpenAI API Key\n",
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+ "openai.api_key = \"key\"\n",
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+ "\n",
129
+ "# Set Paths\n",
130
+ "pdf_path = \"/content/QB-MARATHI.pdf\"\n",
131
+ "source = \"https://transport.maharashtra.gov.in/Site/Upload/Pdf/QB-MARATHI.pdf\"\n",
132
+ "results_folder = \"/content/results\"\n",
133
+ "images_folder = os.path.join(results_folder, \"images\")\n",
134
+ "os.makedirs(results_folder, exist_ok=True)\n",
135
+ "os.makedirs(images_folder, exist_ok=True)\n",
136
+ "\n",
137
+ "# GPT Prompt\n",
138
+ "pre_prompt = \"\"\"Please extract the multiple-choice questions in the attached image in Marathi.\n",
139
+ "There can be one or multiple questions per page.\n",
140
+ "\n",
141
+ "Format the output as:\n",
142
+ "<question_num>Question Number</question_num>\n",
143
+ "<question>Question Text</question>\n",
144
+ "<choices>\n",
145
+ " <choice>A</choice>\n",
146
+ " <choice>B</choice>\n",
147
+ " <choice>C</choice>\n",
148
+ "</choices>\n",
149
+ "<answer>Correct Answer Index (1, 2, or 3)</answer>\n",
150
+ "<image>yes/no</image>\n",
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+ "\n",
152
+ "IMPORTANT:\n",
153
+ "- The <answer> tag should contain ONLY a single integer: 1, 2, or 3.\n",
154
+ "- Do NOT include the actual answer text, only the index.\n",
155
+ "- If no answer is available, leave <answer></answer> empty.\n",
156
+ "- If the question has an associated image (diagram, symbol, road sign), respond with `<image>yes</image>`.\n",
157
+ "- Otherwise, respond with `<image>no</image>`.\n",
158
+ "- If the image contains a reference like 'चित्रात दाखवल्याप्रमाणे' (Marathi for \"as shown in the figure\"), ensure `<image>yes</image>`.\n",
159
+ "- Ensure options are unique and contain at least two valid choices.\n",
160
+ "\"\"\"\n",
161
+ "\n",
162
+ "# Convert PDF to Images\n",
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+ "def convert_pdf_to_images(pdf_path):\n",
164
+ " print(\"📄 Converting PDF to Images...\")\n",
165
+ " images = convert_from_path(pdf_path, dpi=300)\n",
166
+ " image_paths = []\n",
167
+ "\n",
168
+ " for i, image in enumerate(images):\n",
169
+ " img_path = os.path.join(images_folder, f\"page_{i+1}.png\")\n",
170
+ " image.save(img_path, \"PNG\")\n",
171
+ " image_paths.append(img_path)\n",
172
+ "\n",
173
+ " print(f\"✅ {len(image_paths)} images saved.\")\n",
174
+ " return image_paths\n",
175
+ "\n",
176
+ "# Encode Image in Base64\n",
177
+ "def encode_image(image_path):\n",
178
+ " with open(image_path, \"rb\") as image_file:\n",
179
+ " return base64.b64encode(image_file.read()).decode(\"utf-8\")\n",
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+ "\n",
181
+ "# Process Image with GPT-4o\n",
182
+ "def gpt4o_process_image(image_path):\n",
183
+ " base64_image = encode_image(image_path)\n",
184
+ "\n",
185
+ " try:\n",
186
+ " response = openai.ChatCompletion.create(\n",
187
+ " model=\"gpt-4o\",\n",
188
+ " messages=[\n",
189
+ " {\"role\": \"system\", \"content\": pre_prompt},\n",
190
+ " {\"role\": \"user\", \"content\": [\n",
191
+ " {\"type\": \"text\", \"text\": \"Extract all questions from this image.\"},\n",
192
+ " {\"type\": \"image_url\", \"image_url\": {\"url\": f\"data:image/png;base64,{base64_image}\"}}\n",
193
+ " ]}\n",
194
+ " ],\n",
195
+ " max_tokens=2000\n",
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+ " )\n",
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+ "\n",
198
+ " extracted_text = response[\"choices\"][0][\"message\"][\"content\"]\n",
199
+ " return extracted_text\n",
200
+ "\n",
201
+ " except json.JSONDecodeError:\n",
202
+ " print(\"❌ Error: GPT-4o returned an invalid JSON format.\")\n",
203
+ " return None\n",
204
+ "\n",
205
+ "# Parse GPT Response & Fix Issues\n",
206
+ "def parse_gpt_output(response):\n",
207
+ " # Regex patterns for structured extraction\n",
208
+ " q_num_pattern = re.compile(r\"<question_num>(\\d+)</question_num>\")\n",
209
+ " q_pattern = re.compile(r\"<question>(.*?)</question>\")\n",
210
+ " choices_pattern = re.compile(r\"<choices>(.*?)</choices>\", re.DOTALL)\n",
211
+ " answer_pattern = re.compile(r\"<answer>(.*?)</answer>\")\n",
212
+ " image_pattern = re.compile(r\"<image>(.*?)</image>\")\n",
213
+ "\n",
214
+ " # Extract values\n",
215
+ " question_nums = q_num_pattern.findall(response)\n",
216
+ " questions = q_pattern.findall(response)\n",
217
+ " choices_raw = choices_pattern.findall(response)\n",
218
+ " answers_raw = answer_pattern.findall(response)\n",
219
+ " images_required = image_pattern.findall(response)\n",
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+ "\n",
221
+ " # Extract choices correctly & ensure uniqueness\n",
222
+ " choices = []\n",
223
+ " for choice_text in choices_raw:\n",
224
+ " extracted_choices = list(set(re.findall(r\"<choice>(.*?)</choice>\", choice_text))) # Ensure unique choices\n",
225
+ " if len(extracted_choices) < 2: # Validator requires at least two options\n",
226
+ " extracted_choices.append(\"Option Placeholder\") # Add dummy placeholder\n",
227
+ " choices.append(extracted_choices)\n",
228
+ "\n",
229
+ " # Convert to integer (1,2,3) and validate range\n",
230
+ " valid_answers = []\n",
231
+ " for answer in answers_raw:\n",
232
+ " try:\n",
233
+ " int_answer = int(answer.strip())\n",
234
+ " if 1 <= int_answer <= 3: # Ensure valid 1-based index\n",
235
+ " valid_answers.append(int_answer)\n",
236
+ " else:\n",
237
+ " valid_answers.append(None)\n",
238
+ " except ValueError:\n",
239
+ " valid_answers.append(None)\n",
240
+ "\n",
241
+ " # Ensure all lists have the same length\n",
242
+ " min_length = min(len(question_nums), len(questions), len(choices), len(valid_answers), len(images_required))\n",
243
+ " question_nums = question_nums[:min_length]\n",
244
+ " questions = questions[:min_length]\n",
245
+ " choices = choices[:min_length]\n",
246
+ " valid_answers = valid_answers[:min_length]\n",
247
+ " images_required = images_required[:min_length]\n",
248
+ "\n",
249
+ " return question_nums, questions, choices, valid_answers, images_required\n",
250
+ "\n",
251
+ "# Main Execution\n",
252
+ "def main():\n",
253
+ " image_paths = convert_pdf_to_images(pdf_path)\n",
254
+ " all_questions = []\n",
255
+ "\n",
256
+ " for img_path in image_paths:\n",
257
+ " print(f\"📷 Processing {img_path}...\")\n",
258
+ " response = gpt4o_process_image(img_path)\n",
259
+ "\n",
260
+ " if response:\n",
261
+ " q_nums, q_texts, options, correct_answers, images_required = parse_gpt_output(response)\n",
262
+ "\n",
263
+ " for i in range(len(q_nums)):\n",
264
+ " image_info = None\n",
265
+ " image_png = None\n",
266
+ " image_type = None\n",
267
+ "\n",
268
+ " if images_required[i] == \"yes\":\n",
269
+ " image_png = f\"driving-license-marathi-{q_nums[i]}.png\"\n",
270
+ " image_info = \"essential\"\n",
271
+ " image_type = \"diagram\"\n",
272
+ "\n",
273
+ " question_data = {\n",
274
+ " \"language\": \"mr\",\n",
275
+ " \"country\": \"India\",\n",
276
+ " \"file_name\": \"QB-MARATHI.pdf\",\n",
277
+ " \"source\": source,\n",
278
+ " \"license\": \"Education and Research\",\n",
279
+ " \"level\": \"Driver License\",\n",
280
+ " \"category_en\": \"Driving\",\n",
281
+ " \"category_original_lang\": \"ड्रायव्हिंग\",\n",
282
+ " \"original_question_num\": int(q_nums[i]),\n",
283
+ " \"question\": q_texts[i],\n",
284
+ " \"options\": options[i] if i < len(options) else [],\n",
285
+ " \"answer\": correct_answers[i], # ✅ Always 1,2,3\n",
286
+ " \"image_png\": image_png,\n",
287
+ " \"image_information\": image_info,\n",
288
+ " \"image_type\": image_type,\n",
289
+ " \"parallel_question_id\": None\n",
290
+ " }\n",
291
+ " all_questions.append(question_data)\n",
292
+ "\n",
293
+ " # Save as JSON\n",
294
+ " json_path = os.path.join(results_folder, \"marathi_driving_license_valid.json\")\n",
295
+ " with open(json_path, \"w\", encoding=\"utf-8\") as f:\n",
296
+ " json.dump(all_questions, f, indent=4, ensure_ascii=False)\n",
297
+ "\n",
298
+ " # Convert to CSV\n",
299
+ " df = pd.DataFrame(all_questions)\n",
300
+ " csv_path = os.path.join(results_folder, \"marathi_driving_license_valid.csv\")\n",
301
+ " df.to_csv(csv_path, index=False, encoding=\"utf-8\")\n",
302
+ "\n",
303
+ " print(f\"✅ JSON Saved: {json_path}\")\n",
304
+ " print(f\"✅ CSV Saved: {csv_path}\")\n",
305
+ "\n",
306
+ "# Run the script\n",
307
+ "main()\n"
308
+ ],
309
+ "metadata": {
310
+ "colab": {
311
+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "OgERpYUuTV8k",
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+ "outputId": "b67d003f-5647-45e5-9632-46ae8b10c510"
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+ },
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+ "execution_count": 4,
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "📄 Converting PDF to Images...\n",
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+ "✅ 107 images saved.\n",
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+ "📷 Processing /content/results/images/page_1.png...\n",
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+ "📷 Processing /content/results/images/page_2.png...\n",
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+ "✅ JSON Saved: /content/results/QB-MARATHI_valid.json\n",
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+ "✅ CSV Saved: /content/results/QB-MARATHI_valid.csv\n"
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+ ]
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [],
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+ "metadata": {
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+ "id": "tvQrB5J4Ue5Q"
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+ },
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+ "execution_count": null,
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+ "outputs": []
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+ }
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+ ]
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+ }