Acquisition and conversion of video and audio data
Media data is increasingly leveraged in every industrial situation. Work is automated based on analysis of video and audio, and image recognition AI improves the work efficiency. Now, media data including video and audio is essential to machine learning, the development of AI, and other advancements. To develop an AI model that makes the most of media data (e.g., computer vision and audio analysis) or to run a continuous learning cycle of a model, you must build a complicated pipeline that includes data acquisition and conversion to collect media data, make your machine continuously learn models, and deploy new models in automation operation. The intdash-based media data pipeline comprehensively provides mixed functionality required for such digital transformation, including transmission, storage, and conversion of video and audio.
Acquisition of media data such as video and audio has many different challenges including support for various codecs, timestamp matching with other fusion data, and transcoding after collection.
Real-time many-to-many streaming of video data via a server
View DetailsConversion of high-compression video data to an image data format that is easy to use in the annotation process of machine learning
View DetailsAdding integrated timestamps to data streams across multiple sources such as "video and video" or "video and sensor signal" to map data to the same time axis
View DetailsReal-time conversion of video data into streaming formats such as HLS and WebSocket
View DetailsVarious types of audio data including AAC and PCM are supported. Audio data is transmitted and saved as time-series data.
View DetailsYou can build a data pipeline to process collected raw media data for secondary use.
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