
# Cars Tracking
The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan).

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=cars-video-object-tracking) to discuss your requirements, learn about the price and buy the dataset.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F34e8bc05b43e8452019a5163759a1713%2Fframe_000257.png?generation=1687369547730935&alt=media)

# Data Format 
Each video frame from `images` folder is paired with an `annotations.xml` file that meticulously defines the tracking of each vehicle using polygons. 
These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: 
- cars,
- minivans.

The data labeling is visualized in the `boxes` folder.

# Example of the XML-file 
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F459d6e7b97447fc34be0536edd200a7e%2Fcode.png?generation=1687370800622505&alt=media)

# Object tracking is made in accordance with your requirements.

## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=cars-video-object-tracking)** provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**
task_categories:image-segmentation task_categories:image-classification language:en license:cc-by-nc-nd-4.0 code region:us
{"language": ["en"], "license": "cc-by-nc-nd-4.0", "task_categories": ["image-segmentation", "image-classification"], "tags": ["code"], "dataset_info": {"features": [{"name": "image_id", "dtype": "int32"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "annotations", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 614230158, "num_examples": 100}], "download_size": 580108296, "dataset_size": 614230158}}
TAGS
#task_categories-image-segmentation #task_categories-image-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 


# Cars Tracking
The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan).

# Get the dataset

### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.

![](URL

# Data Format 
Each video frame from 'images' folder is paired with an 'URL' file that meticulously defines the tracking of each vehicle using polygons. 
These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: 
- cars,
- minivans.

The data labeling is visualized in the 'boxes' folder.

# Example of the XML-file 
![](URL

# Object tracking is made in accordance with your requirements.

## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: URL

TrainingData's GitHub: URL
# Cars Tracking
The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan). # Get the dataset ### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.

![](URL # Data Format 
Each video frame from 'images' folder is paired with an 'URL' file that meticulously defines the tracking of each vehicle using polygons. 
These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: 
- cars,
- minivans.

The data labeling is visualized in the 'boxes' folder. # Example of the XML-file 
![](URL # Object tracking is made in accordance with your requirements. ## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: URL

TrainingData's GitHub: URL
TAGS
#task_categories-image-segmentation #task_categories-image-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
 # Cars Tracking
The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan). # Get the dataset ### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.

![](URL # Data Format 
Each video frame from 'images' folder is paired with an 'URL' file that meticulously defines the tracking of each vehicle using polygons. 
These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: 
- cars,
- minivans.

The data labeling is visualized in the 'boxes' folder. # Example of the XML-file 
![](URL # Object tracking is made in accordance with your requirements. ## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: URL

TrainingData's GitHub: URL
passage: TAGS
#task_categories-image-segmentation #task_categories-image-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
# Cars Tracking
The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan).# Get the dataset### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.

![](URL# Data Format 
Each video frame from 'images' folder is paired with an 'URL' file that meticulously defines the tracking of each vehicle using polygons. 
These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: 
- cars,
- minivans.

The data labeling is visualized in the 'boxes' folder.# Example of the XML-file 
![](URL# Object tracking is made in accordance with your requirements.## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: URL

TrainingData's GitHub: URL