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--- |
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license: mit |
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task_categories: |
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- visual-question-answering |
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language: |
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- en |
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tags: |
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- Traffic_Signal_Recognition |
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size_categories: |
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- 1K<n<10K |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: id |
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dtype: int64 |
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- name: image_name |
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dtype: string |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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- name: ' traffic_sign' |
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dtype: string |
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- name: image |
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dtype: image |
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splits: |
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- name: train |
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num_bytes: 159624173.688 |
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num_examples: 3472 |
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- name: test |
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num_bytes: 39973129.0 |
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num_examples: 869 |
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download_size: 193968286 |
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dataset_size: 199597302.688 |
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--- |
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🧭 Overview |
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Indian Traffic VQA is a real-world Visual Question Answering (VQA) dataset focusing on Indian road traffic signboards. |
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The dataset is designed for training and evaluating Vision-Language Models (VLMs) and VQA systems in the traffic and transportation domain. |
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This dataset bridges a gap between real-world Indian traffic conditions and machine understanding — ideal for research in autonomous driving, smart city AI, and traffic sign recognition under natural environments. |
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________________________________________ |
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📦 Dataset Summary |
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• Images: 1,085 real-world traffic signboard images |
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• Questions: 4,341 unique questions |
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• Answers: Short, ground-truth textual responses |
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• Source: All images were collected using a mobile phone in real Indian road environments |
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• Format: .csv file with the following columns: |
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o image_name — name of the image file |
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o question — text-based query |
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o answer — corresponding ground-truth answer |
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________________________________________ |
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🧠 Task Definition |
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Given an image of a traffic signboard and a related question, the model must predict a short text answer. |
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Example: |
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image_name question answer |
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imag_00001.jpg What does this sign indicate? Speed Limit |
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img_00002.jpg What does this sign show? Stop |
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img_00003.jpg Is U-turn allowed here? No |
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________________________________________ |
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🧩 Applications |
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• Visual Question Answering (VQA) |
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• Vision-Language Model (VLM) Fine-tuning |
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• Multimodal classification of traffic signs |
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• Dataset for benchmarking model reasoning in domain-specific visual data |
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________________________________________ |
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🧰 Data Collection Details |
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• Captured in diverse Indian traffic conditions (urban, rural, highways) |
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• Includes varying lighting, occlusions, and view angles |
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• All images are real photographs, not synthetic |
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________________________________________ |
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⚖️ License |
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You may distribute, modify, or use this dataset for non-commercial research purposes. |
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Please give appropriate credit by citing this dataset. |
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________________________________________ |
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The .zip file contains all the 1085 images with 512x512 resolution. |
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There are two .csv files attached. |
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traffic_vqa_1085.csv contains one question and one answer, |
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traffic_vqa_4341.csv contains multiple questions and answers per image. |
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The first .csv file can be used for low resource computational environment. |
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________________________________________ |
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🚀 Future Work |
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Future releases will include: |
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• Regional signboard subsets (state-specific) |
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• Video-based question answering |
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• Multilingual question support (English + Hindi) |
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________________________________________ |
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👥 Contributors |
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🧠 Data Curators |
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🧩 Chandra Mohan Bhuma |
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🧩 CH.V.M.S.N. Pavan Kumar |
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🧩 T. Krishna Chaitanya |
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🧩 Miriyala Suneel |
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📷 Data Collectors |
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📸 Perumalla Himasri |
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📸 Vallapuneni Venkata Siva Kumar |
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📸 Ratna Seethal Saripalli |
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📸 Somanapalli Hindu |
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