N+1 fish, N+2 fish dataset (train_videos)
N+1 fish, N+2 fish

train_videos (2664 files)
ZzNv0x8nujQXuz35.mp4 51.69MB
zZCiaXh6FllAYILs.mp4 46.21MB
ZzNv0x8nujQXuz35.json 18.75kB
ZZ4qcDCvrB2ThFu6.json 5.44kB
ZZ4qcDCvrB2ThFu6.mp4 21.30MB
zZCiaXh6FllAYILs.json 12.53kB
ZyWVWGHjmzX4vBbE.json 20.58kB
ZyWVWGHjmzX4vBbE.mp4 83.45MB
zXZSvmqfqvnwJgn1.mp4 38.21MB
ZYs9NeGe4Y472z0p.json 4.46kB
ZYs9NeGe4Y472z0p.mp4 46.98MB
zxjr6V8bFiFHxpNU.json 9.22kB
zxjr6V8bFiFHxpNU.mp4 30.84MB
zXZSvmqfqvnwJgn1.json 8.99kB
ZVg07UANwbxMkOpk.mp4 67.38MB
zVTfNIDEQIXpfRTu.json 5.44kB
zVTfNIDEQIXpfRTu.mp4 21.77MB
ZTARQcOnbBIY8Mgy.json 5.37kB
ZTARQcOnbBIY8Mgy.mp4 22.83MB
ZVg07UANwbxMkOpk.json 14.19kB
ZSSevmaFvBKXtUkX.mp4 24.89MB
ZT3F0L0a4gyz1i2p.json 22.98kB
ZT3F0L0a4gyz1i2p.mp4 67.83MB
zS1CWBe6SQZPQ56Y.json 4.70kB
zS1CWBe6SQZPQ56Y.mp4 47.89MB
ZSSevmaFvBKXtUkX.json 7.10kB
zR6VkJBSdt1ZrAEx.mp4 123.96MB
zrqy3XarL6jSoraK.json 1.65kB
zrqy3XarL6jSoraK.mp4 5.41MB
zR3vz986JhrV8VXA.mp4 14.86MB
zR6VkJBSdt1ZrAEx.json 32.10kB
zqWCbHoUPI9lMVBK.json 18.23kB
zqWCbHoUPI9lMVBK.mp4 105.48MB
zR3vz986JhrV8VXA.json 2.84kB
zPtOCQYZ330dffkt.mp4 5.54MB
Zqp3yxvsMHRCcU4L.json 6.63kB
Zqp3yxvsMHRCcU4L.mp4 58.33MB
ZpQfx3wAesvyITIS.mp4 18.45MB
zPtOCQYZ330dffkt.json 1.91kB
ZPmh03ifDug1fyt6.json 10.79kB
ZPmh03ifDug1fyt6.mp4 80.77MB
ZpQfx3wAesvyITIS.json 4.74kB
ZNpJ6Y0hxxhNPEuS.mp4 153.71MB
zP3VySyM54eyj5mZ.json 48.62kB
zP3VySyM54eyj5mZ.mp4 162.94MB
zN0R9OrjupOmzpmZ.json 7.81kB
zN0R9OrjupOmzpmZ.mp4 61.04MB
ZNpJ6Y0hxxhNPEuS.json 5.42kB
zmYfc0lC2MQ3gfrW.mp4 90.28MB
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Type: Dataset
Tags:

Bibtex:
@article{,
title= {N+1 fish, N+2 fish dataset (train_videos)},
journal= {},
author= {N+1 fish, N+2 fish},
year= {},
url= {https://www.drivendata.org/competitions/48/identify-fish-challenge},
abstract= {Our video data was collected for an ongoing monitoring project involving our partners at The Nature Conservancy-Massachusetts (TNC) and the Gulf of Maine Research Institute (GMRI). We worked with the fishermen to create a dataset of video footage from different boats that can be released to the public. 

The video data is in the form of standard and well supported MP4 v2 format with H.264 compression. These videos are on average 35 minutes long at a resolution of 640x480 and and vary between 150MB to 550MB in size. We will also provide cropped fish images to aid in training complementary models. Our annotations will be categorial with each fish having a single species. 

There are six species of interest for this competition, which appear in a non-balanced proportion. As we aim to achieve performance on each of these species, we will be compiling a data set that is mostly balanced across these species. Complicating factors include different catch distributions across different vessels, which can have an adverse performance on the types of algorithms submitted if people attempt to game the system by parameterizing these distributions. We are attempting to balance the data set by providing at least 100 unique fish for each species within the videos from multiple vessels.




![](https://i.imgur.com/qHK6WUz.png)

![](https://i.imgur.com/T7UDAJA.png)},
keywords= {},
terms= {},
license= {},
superseded= {}
}


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