
# Grocery Shelves Dataset
## Facing is the process of arranging products on shelves and counters. 
The dataset consist of labeled photographs of grocery store shelves. 
The Grocery Shelves Dataset can be used to analyze and optimize product placement data, develop strategies for increasing product visibility, maximize the effectiveness of the product placements and increase sales.

# 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=grocery-shelves-dataset) 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%2Ffe8b57fae6e4b470249446606b480243%2Ffaaaa.png?generation=1686606203731941&alt=media)

# Dataset structure
- **img** - contains of original images of grocery store shelves
- **labels** - includes polyline labeling for the original images
-  **annotations.xml** -  contains coordinates of the polylines 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 polylines for product placement. For each point, the x and y coordinates are provided.

### Attributes
- **is_flipped** - the product position (*true* if the product is flipped)
- **is_facing** - the product visability (*true* if the product's cover is turned towards us and can be clearly seen)

# Example of XML file structure
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F95f4760eb38df78cb6b13303b5758d38%2Fcarbon%20(8).png?generation=1686606438563238&alt=media)

# Product Facing might be made in accordance with your requirements.

## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=grocery-shelves-dataset) 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 language:en license:cc-by-nc-nd-4.0 code finance region:us
{"language": ["en"], "license": "cc-by-nc-nd-4.0", "task_categories": ["image-segmentation"], "tags": ["code", "finance"], "dataset_info": {"features": [{"name": "image_id", "dtype": "uint32"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "shapes", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 37976724, "num_examples": 16}], "download_size": 37970716, "dataset_size": 37976724}}
TAGS
#task_categories-image-segmentation #language-English #license-cc-by-nc-nd-4.0 #code #finance #region-us 


# Grocery Shelves Dataset
## Facing is the process of arranging products on shelves and counters. 
The dataset consist of labeled photographs of grocery store shelves. 
The Grocery Shelves Dataset can be used to analyze and optimize product placement data, develop strategies for increasing product visibility, maximize the effectiveness of the product placements and increase sales.

# 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 grocery store shelves
- labels - includes polyline labeling for the original images
-  URL -  contains coordinates of the polylines 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 polylines for product placement. For each point, the x and y coordinates are provided.

### Attributes
- is_flipped - the product position (*true* if the product is flipped)
- is_facing - the product visability (*true* if the product's cover is turned towards us and can be clearly seen)

# Example of XML file structure
![](URL

# Product Facing 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
# Grocery Shelves Dataset ## Facing is the process of arranging products on shelves and counters. 
The dataset consist of labeled photographs of grocery store shelves. 
The Grocery Shelves Dataset can be used to analyze and optimize product placement data, develop strategies for increasing product visibility, maximize the effectiveness of the product placements and increase sales. # 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 grocery store shelves
- labels - includes polyline labeling for the original images
-  URL -  contains coordinates of the polylines 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 polylines for product placement. For each point, the x and y coordinates are provided. ### Attributes
- is_flipped - the product position (*true* if the product is flipped)
- is_facing - the product visability (*true* if the product's cover is turned towards us and can be clearly seen) # Example of XML file structure
![](URL # Product Facing 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-segmentation #language-English #license-cc-by-nc-nd-4.0 #code #finance #region-us 
 # Grocery Shelves Dataset ## Facing is the process of arranging products on shelves and counters. 
The dataset consist of labeled photographs of grocery store shelves. 
The Grocery Shelves Dataset can be used to analyze and optimize product placement data, develop strategies for increasing product visibility, maximize the effectiveness of the product placements and increase sales. # 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 grocery store shelves
- labels - includes polyline labeling for the original images
-  URL -  contains coordinates of the polylines 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 polylines for product placement. For each point, the x and y coordinates are provided. ### Attributes
- is_flipped - the product position (*true* if the product is flipped)
- is_facing - the product visability (*true* if the product's cover is turned towards us and can be clearly seen) # Example of XML file structure
![](URL # Product Facing 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-segmentation #language-English #license-cc-by-nc-nd-4.0 #code #finance #region-us 
# Grocery Shelves Dataset## Facing is the process of arranging products on shelves and counters. 
The dataset consist of labeled photographs of grocery store shelves. 
The Grocery Shelves Dataset can be used to analyze and optimize product placement data, develop strategies for increasing product visibility, maximize the effectiveness of the product placements and increase sales.# 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 grocery store shelves
- labels - includes polyline labeling for the original images
-  URL -  contains coordinates of the polylines 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 polylines for product placement. For each point, the x and y coordinates are provided.### Attributes
- is_flipped - the product position (*true* if the product is flipped)
- is_facing - the product visability (*true* if the product's cover is turned towards us and can be clearly seen)# Example of XML file structure
![](URL# Product Facing 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