
# Basketball Tracking
## Tracking is a deep learning process where the algorithm tracks the movement of an object. 
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. 
The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame.

# 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=basketball_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%2Ffebc78a960385a4fd6a0242b58c4056d%2Fbb.png?generation=1686731703497308&alt=media)

# Dataset structure
- **img** - contains of original images of basketball players.
- **boxes** - includes bounding box labeling for a ball in the original images.
-  **annotations.xml** -  contains coordinates of the boxes and labels, created for the original photo

# Data Format

Each image from `img` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided.

### Attributes
- **occluded** - the ball visability (*true* if the the ball is occluded by 30%)
- **basket** - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area)

# Example of XML file structure
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0d5c79a67be4c702b12540906b72c240%2Fcarbon.png?generation=1686731488719900&alt=media)

# Basketball Tracking might be made in accordance with your requirements.

## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=basketball_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-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-classification"], "tags": ["code"], "dataset_info": {"features": [{"name": "image_id", "dtype": "int32"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "shapes", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 191244976, "num_examples": 70}], "download_size": 191271989, "dataset_size": 191244976}}
TAGS
#task_categories-image-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 


# Basketball Tracking
## Tracking is a deep learning process where the algorithm tracks the movement of an object. 
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. 
The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame.

# 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

# Dataset structure
- img - contains of original images of basketball players.
- boxes - includes bounding box labeling for a ball in the original images.
-  URL -  contains coordinates of the boxes and labels, created for the original photo

# Data Format

Each image from 'img' folder is accompanied by an XML-annotation in the 'URL' file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided.

### Attributes
- occluded - the ball visability (*true* if the the ball is occluded by 30%)
- basket - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area)

# Example of XML file structure
![](URL

# Basketball Tracking might be 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
# Basketball Tracking ## Tracking is a deep learning process where the algorithm tracks the movement of an object. 
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. 
The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame. # 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 # Dataset structure
- img - contains of original images of basketball players.
- boxes - includes bounding box labeling for a ball in the original images.
-  URL -  contains coordinates of the boxes and labels, created for the original photo # Data Format

Each image from 'img' folder is accompanied by an XML-annotation in the 'URL' file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided. ### Attributes
- occluded - the ball visability (*true* if the the ball is occluded by 30%)
- basket - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area) # Example of XML file structure
![](URL # Basketball Tracking might be 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-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
 # Basketball Tracking ## Tracking is a deep learning process where the algorithm tracks the movement of an object. 
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. 
The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame. # 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 # Dataset structure
- img - contains of original images of basketball players.
- boxes - includes bounding box labeling for a ball in the original images.
-  URL -  contains coordinates of the boxes and labels, created for the original photo # Data Format

Each image from 'img' folder is accompanied by an XML-annotation in the 'URL' file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided. ### Attributes
- occluded - the ball visability (*true* if the the ball is occluded by 30%)
- basket - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area) # Example of XML file structure
![](URL # Basketball Tracking might be 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-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
# Basketball Tracking## Tracking is a deep learning process where the algorithm tracks the movement of an object. 
The dataset consist of screenshots from videos of basketball games with the ball labeled with a bounging box. 
The dataset can be used to train a neural network in ball control recognition. The dataset is useful for automating the camera operator's work during a match, allowing the ball to be efficiently kept in frame.# 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# Dataset structure
- img - contains of original images of basketball players.
- boxes - includes bounding box labeling for a ball in the original images.
-  URL -  contains coordinates of the boxes and labels, created for the original photo# Data Format

Each image from 'img' folder is accompanied by an XML-annotation in the 'URL' file indicating the coordinates of the bounding boxes for the ball position. For each point, the x and y coordinates are provided.### Attributes
- occluded - the ball visability (*true* if the the ball is occluded by 30%)
- basket - the position related to the basket (*true* if the ball is covered with a basket on any distinguishable area)# Example of XML file structure
![](URL# Basketball Tracking might be 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