70-Page Report on the COCO Dataset and Object Detection [Part 1]

Take a look at the  to quickly find common resources and/or assets for a given dataset and a specific task, in this case dataset=COCO, task=object detection. We are building a dataset-first marketplace focusing on the end-to-end machine learning pipeline, one where data and assets can be shared and traded. The marketplace will contain all that the  contains (and much more for a lot more datasets)

1. Part 1 (this one): COCO Summary Card. Each link will take you to the longer report where you can learn more. The next 3 parts represent a specific section in the report.
2. Part 2: This part is about COCO and examples and tutorials of tools and platforms used to work with COCO (or object detection tasks).
3. Part 3: Process: This part is about the tools and platforms that can be used for different phases of data preparate or data processing involved in vision, object detection, and specifically COCO-related tasks. It will also discuss synthetic data and data quality.
4. Part 4: Models: This part is about a quick introduction to some pre-trained models and some corresponding readings.

COCO Summary Card

 (Common Objects in Context)

• Website: 
• Github: 
• Paper: 

dataset with evaluation metric Average Precision (AP)

: Object Detection, Panoptic Semantic Segmentation, Keypoint Detection, DensePose

: Tools and platforms used to work with COCO (or object detection tasks)

• FiftyOne, DataTorch, Know Your Data (KYD), OpenCV, OpenVINO, CVAT, Roboflow, SuperAnnotate, OpenMMLab, Coral, Amazon, Facebook, Google, Microsoft, NVIDIA, Weights and Biases.

  
  

: Open-source tools and Paid platforms to perform the following steps.

• : CVAT, LabelImg, Label Studio, Makesense.AI, OpenLabeling, Dataloop, Hive Data, Labelbox, Scale AI, SuperAnnotate, V7, Ximilar

• : Albumentations, AugLy, Augmentor, autoalbument, DALI, Data Augmentation for Object Detection, Imgaug, Kornia, MXNet, Tensorflow, Transforms (PyTorch)

• : Cvedia, Neurolabs, Synthesis AI, Unity, UnrealROX

• 
  

: To answer what objects are in image X and where are they? (You’ll find a brief summary and readings.)

If you have feedback please review this link () and email me at [email protected]. Looking forward to starting a conversation.

Next, Part 2