This dataset contains all COCO 2017 images and annotations split in training (118287 images) and validation (5000 images).

coco2017

Image-text pairs from MS COCO2017.

  Data origin

Data originates from cocodataset.org While coco-karpathy uses a dense format (with several sentences and sendids per row), coco-karpathy-long uses a long format with one sentence (aka caption) and sendid per row. coco-karpathy-long uses the first five sentences and therefore is five times as long as coco-karpathy. phiyodr/coco2017: One row corresponds one image with several sentences. phiyodr/coco2017-long: One row… See the full description on the dataset page: https://huggingface.co/datasets/phiyodr/coco2017.

Microsoft COCO 2017 Dataset

## Overview

Microsoft COCO 2017 Dataset is a dataset for object detection tasks - it contains Coco Objects annotations for 2,245 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

📄 License and Attribution

This dataset is a downsampled version of the COCO 2017 dataset, tailored for segmentation tasks. It has the following fields:

image: 256x256 image segmentation: 256x256 image. Each pixel encodes the class of that pixel. See class_names_dict.json for a legend. captions: a list of captions for the image, each by a different labeler.

Use the dataset as follows: import requests from datasets import load_dataset

ds =… See the full description on the dataset page: https://huggingface.co/datasets/peteole/coco2017-segmentation-50k-256x256.

Coco 2017

## Overview

Coco 2017 is a dataset for object detection tasks - it contains Fruits annotations for 10,596 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

The dataset used in the paper is the MS-COCO 2017 detection dataset.

This is the full 2017 COCO object detection dataset (train and valid), which is a subset of the most recent 2020 COCO object detection dataset.

COCO is a large-scale object detection, segmentation, and captioning dataset of many object types easily recognizable by a 4-year-old. The data is initially collected and published by Microsoft. The original source of the data is here and the paper introducing the COCO dataset is here.

COCO 2017 Dataset for Image Colorization

  Overview

This dataset is derived from the COCO (Common Objects in Context) 2017 dataset, which is a large-scale object detection, segmentation, and captioning dataset. The COCO 2017 dataset has been adapted here specifically for the task of image colorization.

  Format

DatasetDict({ train: Dataset({ features: ['license', 'file_name', 'coco_url', 'height', 'width', 'date_captured', 'flickr_url', 'image_id'… See the full description on the dataset page: https://huggingface.co/datasets/nickpai/coco2017-colorization.

This dataset is a custom dataset made in accordance with the COCO2017 standard for training XCT images of biaxial non-crimp Fabric-reinforced polymer composites with different degrees of damage

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The MS-COCO 2017 test-dev17 dataset is used to evaluate the performances of various RefineDet networks.

COCO 2017 Cats

## Overview

COCO 2017 Cats is a dataset for object detection tasks - it contains Cats annotations for 4,112 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Probably the most widely used dataset today for object localization is COCO: Common Objects in Context. Provided here are all the files from the 2017 version, along with an additional subset dataset created by fast.ai. Details of each COCO dataset is available from the COCO dataset page. The fast.ai subset contains all images that contain one of five selected categories, restricting objects to just those five categories; the categories are: chair couch tv remote book vase.

Dataset

This dataset was created by jcoral

Contents

The COCO-MLT is created from MS COCO-2017, containing 1,909 images from 80 classes. The maximum of training number per class is 1,128 and the minimum is 6. We use the test set of COCO2017 with 5,000 for evaluation. The ratio of head, medium, and tail classes is 22:33:25 in COCO-MLT.

MJ-COCO-2025 is a modified version of the MS-COCO-2017 dataset, in which the annotation errors have been automatically corrected using model-driven methods. The name "MJ" originates from the initials of Min Je Kim, the individual who updated the dataset. "MJ" also stands for "Modification & Justification," emphasizing that the modifications were not manually edited but were systematically validated through machine learning models to increase reliability and quality. Thus, MJ-COCO-2025 reflects both a personal identity and a commitment to improving the dataset through thoughtful modification, ensuring improved accuracy, reliability and consistency. The comparative results of MS-COCO and MJ-COCO datasets are presented in Table 1 and Figure 1. The MJ-COCO-2025 dataset features the improvements, including fixes for group annotations, addition of missing annotations, removal of redundant or overlapping labels, etc. These refinements aim to improve training and evaluation performance in object detection tasks.

Summary of Improvements:

The re-labeled MJ-COCO-2025 dataset demonstrates substantial improvements in annotation quality, with significant increases in several categories and minor corrections in a few due to previous over-annotations or misclassifications, as shown in Table 1 when compared to the original MS-COCO-2017 dataset.

Table 1: Comparison of Class-wise Annotations: MS-COCO-2017 and MJ-COCO-2025. Class Names | MS-COCO | MJ-COCO | Difference | Class Names | MS-COCO | MJ-COCO | Difference ---------------------|---------|---------|------------|----------------------|---------|---------|------------ Airplane | 5,135 | 5,810 | 675 | Kite | 9,076 | 15,092 | 6,016 Apple | 5,851 | 19,527 | 13,676 | Knife | 7,770 | 6,697 | -1,073 Backpack | 8,720 | 10,029 | 1,309 | Laptop | 4,970 | 5,280 | 310 Banana | 9,458 | 49,705 | 40,247 | Microwave | 1,673 | 1,755 | 82 Baseball Bat | 3,276 | 3,517 | 241 | Motorcycle | 8,725 | 10,045 | 1,320 Baseball Glove | 3,747 | 3,440 | -307 | Mouse | 2,262 | 2,377 | 115 Bear | 1,294 | 1,311 | 17 | Orange | 6,399 | 18,416 | 12,017 Bed | 4,192 | 4,177 | -15 | Oven | 3,334 | 4,310 | 976 Bench | 9,838 | 9,784 | -54 | Parking Meter | 1,285 | 1,355 | 70 Bicycle | 7,113 | 7,853 | 740 | Person | 262,465 | 435,252 | 172,787 Bird | 10,806 | 13,346 | 2,540 | Pizza | 5,821 | 6,049 | 228 Boat | 10,759 | 13,386 | 2,627 | Potted Plant | 8,652 | 11,252 | 2,600 Book | 24,715 | 35,712 | 10,997 | Refrigerator | 2,637 | 2,728 | 91 Bottle | 24,342 | 32,455 | 8,113 | Remote | 5,703 | 5,428 | -275 Bowl | 14,358 | 13,591 | -767 | Sandwich | 4,373 | 3,925 | -448 Broccoli | 7,308 | 14,275 | 6,967 | Scissors | 1,481 | 1,558 | 77 Bus | 6,069 | 7,132 | 1,063 | Sheep | 9,509 | 12,813 | 3,304 Cake | 6,353 | 8,968 | 2,615 | Sink | 5,610 | 5,969 | 359 Car | 43,867 | 51,662 | 7,795 | Skateboard | 5,543 | 5,761 | 218 Carrot | 7,852 | 15,411 | 7,559 | Skis | 6,646 | 8,945 | 2,299 Cat | 4,768 | 4,895 | 127 | Snowboard | 2,685 | 2,565 | -120 Cell Phone | 6,434 | 6,642 | 208 | Spoon | 6,165 | 6,156 | -9 Chair | 38,491 | 56,750 | 18,259 | Sports Ball | 6,347 | 6,060 | -287 Clock | 6,334 | 7,618 | 1,284 | Stop Sign | 1,983 | 2,684 | 701 Couch | 5,779 | 5,598 | -181 | Suitcase | 6,192 | 7,447 | 1,255 Cow | 8,147 | 8,990 | 843 | Surfboard | 6,126 | 6,175 | 49 Cup | 20,650 | 22,545 | 1,895 | Teddy Bear | 4,793 | 6,432 | 1,639 Dining Table | 15,714 | 16,569 | 855 | Tennis Racket | 4,812 | 4,932 | 120 Dog | 5,508 | 5,870 | 362 | Tie | 6,496 | 6,048 | -448 Donut | 7,179 | 11,622 | 4,443 | Toaster | 225 | 320 | 95 Elephant | 5,513 | 6,233 | 720 | Toilet | 4,157 | 4,433 | 276 Fire Hydrant ...

A BitTorrent file to download data with the title 'COCO 2017 Resized to 256x256'

Original dataset credit: https://cocodataset.org/#home

Dataset

This dataset was created by Aishwary Dewangan

Released under Data files © Original Authors

Contents

baohao/coco2017 dataset hosted on Hugging Face and contributed by the HF Datasets community