COCO is a large-scale object detection, segmentation, and captioning dataset. The dataset classes include 80 pre-trained objects. 
Website: https://cocodataset.org/ 
Github: cocodataset/cocodataset.github.io
Paper: Microsoft COCO: Common Objects in Context
API: COCO API
 
This is a *benchmark dataset* for the following tasks and evaluation metric:
	
Task: Object Detection; Evaluation metric:  Average Precision (AP)
	
Task: Panoptic Semantic Segmentation; Evaluation metric: Panoptic Quality (PQ)
	
Task: Keypoint Detection; Evaluation metric: Object Keypoint Similarity (OKS)
	
Task: DensePose; Evaluation metric: multiple metrics
 
Other products that will be linked to this dataset will be open-source tools, paid platforms, papers, readings, and tutorials to:
	
Explore COCO dataset (or object detection tasks)
	
	
Create and process COCO dataset (or datasets for object detection tasks)
	
		
		
Data collection
		
		
		
Data labeling and annotation
		
		
		
Data cleaning
		
		
		
Data transformations
		
		
		
Data visualization
		
		
		
Synthetic data
		
		
		
Data quality
		
	
	
	
	
Train and model using COCO dataset (or datasets for object detection tasks, i.e. answer what objects are in image X and where are they?
	
	
	
Finetune and build custome datasets and object detection applications