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README.md

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+---
+license: apache-2.0
+task_categories:
+- video-classification
+- question-answering
+- visual-question-answering
+tags:
+- perception-test
+- video-qa
+- multiple-choice
+- video-understanding
+size_categories:
+- 1K<n<10K
+viewer: true
+---
+
+# Perception Test MCQ Dataset
+
+## Dataset Description
+
+This dataset contains **1000 video question-answering entries** from the Perception Test dataset. Each entry includes a video and a multiple-choice question about the video content, testing various aspects of video understanding including object tracking, action recognition, and temporal reasoning.
+
+## Dataset Structure
+
+This dataset follows the VideoFolder format with the following structure:
+
+```
+dataset/
+├── data/
+│   ├── videos/
+│   │   ├── video_XXX.mp4
+│   │   └── ...
+│   └── metadata.csv
+└── README.md
+```
+
+### Metadata Format
+
+The `metadata.csv` contains:
+- `file_name`: Path to the video file (relative to split directory)
+- `video_id`: Unique video identifier
+- `question`: The question text
+- `options`: JSON string containing multiple choice options
+- `correct_answer`: The correct answer (available for 997/1000 entries)
+- `question_type`: Type of question (typically "multiple choice")
+
+## Dataset Statistics
+
+- **Total QA pairs**: 1000
+- **Unique videos**: 1000
+- **Average questions per video**: 1.0
+- **Entries with answers**: 997/1000 (99.7%)
+- **Video format**: MP4
+
+### Question Type Distribution
+
+- `unknown`: 1000 questions
+
+## Usage
+
+### Loading the Dataset
+
+```python
+from datasets import load_dataset
+import json
+
+# Load the dataset
+dataset = load_dataset("advaitgupta/perception_test_mcq")
+
+# Access the data split
+data = dataset['data']
+
+# Example: Get first sample
+sample = data[0]
+print("Question:", sample['question'])
+print("Options:", json.loads(sample['options']))
+print("Correct Answer:", sample['correct_answer'])
+print("Video:", sample['file_name'])
+```
+
+### Processing Videos and Questions
+
+```python
+import json
+import cv2
+
+# Load metadata
+metadata = data.to_pandas()
+
+# Process a video-question pair
+sample = metadata.iloc[0]
+video_path = sample['file_name']
+question = sample['question']
+options = json.loads(sample['options'])
+correct_answer = sample['correct_answer']
+
+print(f"Question: {question}")
+for i, option in enumerate(options):
+    print(f"{i+1}. {option}")
+print(f"Correct Answer: {correct_answer}")
+
+# Load and process video
+cap = cv2.VideoCapture(video_path)
+# ... your video processing code
+```
+
+## Task Types
+
+This dataset covers various video understanding tasks:
+
+### Object and Action Recognition
+*"What ingredients did the person put in the bowl or on the plate?"*
+
+### Temporal Reasoning
+*"How many objects were put in the backpack throughout the video?"*
+
+### Camera Motion Analysis
+*"Is the camera moving or static?"*
+
+### Spatial Understanding
+*"Where is the person?"*
+
+### Activity Recognition
+*"What is the person preparing?"*
+
+## Data Quality
+
+- All video files have been validated to exist
+- Questions are human-annotated from the Perception Test dataset
+- Multiple choice format ensures consistent evaluation
+- Fair distribution across videos (avg 1.0 questions per video)
+- Correct answers provided for evaluation
+
+## Example Entry
+
+```json
+{
+  "file_name": "videos/video_10909.mp4",
+  "video_id": "video_10909",
+  "question": "Is the camera moving or static?",
+  "options": ["I don't know", "moving", "static or shaking"],
+  "correct_answer": "static or shaking",
+  "question_type": "multiple choice"
+}
+```
+
+## Citation
+
+If you use this dataset, please cite the original Perception Test paper:
+
+```bibtex
+@article{perception-test-2022,
+  title={Perception Test: A Diagnostic Benchmark for Multimodal Video Models},
+  author={Pătrăucean, Viorica and others},
+  journal={arXiv preprint arXiv:2211.13775},
+  year={2022}
+}
+```
+
+## License
+
+This dataset is released under the Apache 2.0 license.

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