2nd Batch

## Overview

2nd Batch is a dataset for object detection tasks - it contains Object annotations for 1,528 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).

4 Batch

## Overview

4 Batch is a dataset for object detection tasks - it contains Sperm annotations for 1,593 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).

RacconDog Image Batch

## Overview

RacconDog Image Batch is a dataset for object detection tasks - it contains Animals annotations for 218 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).

albertvillanova/tmp-struct-batch dataset hosted on Hugging Face and contributed by the HF Datasets community

Batch export all podcasts or episodes by full-text keyword search, e.g., people, brands, topics...

LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned.

Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the .map() function as follows:

import soundfile as sf

def map_to_array(batch):
  speech_array, _ = sf.read(batch["file"])
  batch["speech"] = speech_array
  return batch

dataset = dataset.map(map_to_array, remove_columns=["file"])

This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books in English. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours.

Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .wav format and is not converted to a float32 array. To convert the audio file to a float32 array, please make use of the .map() function as follows:

import soundfile as sf

def map_to_array(batch):
  speech_array, _ = sf.read(batch["file"])
  batch["speech"] = speech_array
  return batch

dataset = dataset.map(map_to_array, remove_columns=["file"])

Set of COVADIS tables for exceptional transport management in the Sarthe Department(72)

Data set for strategic noise maps of Charente’s terrestrial transport infrastructure. Data for 24H weighted average sound graduation cards (type A) greater than 55 dB(A) or nocturnal scales greater than 50 dB(A) are included; the 24-hour or night weighted average limit values (type C) maps; type B maps from the sound classification of roadways and railways. The Charente is not affected by known or foreseeable sound evolution maps (type D).