Update README.md

README.md

@@ -14,4 +14,41 @@ tags:
 - prediction
 size_categories:
 - 1K<n<10K
----
+---
+
+# Nexar Collision Prediction Dataset
+
+## Dataset
+
+The Nexar collision prediction dataset comprises videos from Nexar dashcams. Videos have a resolution of 1280x720 at 30 frames per second and typically have about 40 seconds of duration. The dataset contains 1500 videos where half show events where there was a collision or a collision was eminent (positive cases), and the other half shows regular driving (negative cases). The time of the event (collision or near-miss) is available for positive cases.
+
+
+## Goal
+
+The goal of this dataset is to help build models to predict the time of collision. Models should be able to predict if a collision is about to happen or not. Both collisions and near-misses are treated equally as positive cases.
+
+
+## Model assessment
+
+Models should be able to predict that a collision is about to happen as soon as possible, while avoiding false positives. Assessment scripts will be made available shortly that calculate the mean average precision across different times before collision (e.g. 500ms, 1000ms, 2000ms).
+
+
+## Usage
+
+``` python
+from datasets import load_dataset
+
+dataset = load_dataset("videofolder", data_dir="/your/path/nexar_collision_prediction", split="train", drop_labels=False)
+```
+
+A positive example would look like this:
+
+``` bash
+{'video': <decord.video_reader.VideoReader object at 0x7f127b56f940>, 'label': 1, 'time_of_event': 19.967}
+```
+
+and a negative example like this:
+
+``` bash
+{'video': <decord.video_reader.VideoReader object at 0x7f127b56f250>, 'label': 0, 'time_of_event': None}
+```