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I should be able to search for videos or images, e.g. by the title of the image or video, by geo-coordinates, also with the context of the video and so on.
When I use nesis to analyse videos, I want the following types of information to be extracted or analysed, depending on my goals or application. Here are some common types of information I want nesis to output from the videos and images:
Video specification
Object Detection and Tracking: Identify and track objects or people within the video frame over time. This could include detecting vehicles, pedestrians, animals, or specific objects of interest.
Action Recognition: Recognize human actions or activities depicted in the video, such as walking, running, sitting, or gestures.
Facial Recognition: Identify and recognize faces of individuals appearing in the video, potentially matching them against a database of known individuals.
Emotion Recognition: Analyze facial expressions to infer the emotional state of individuals within the video, such as happiness, sadness, anger, or surprise.
Speech Recognition and Transcription: Convert spoken words within the video into text, enabling transcription and analysis of dialogue or speech content.
Scene Understanding: Understand the overall context or scene depicted in the video, such as indoor or outdoor settings, specific locations, or environmental conditions.
Object Localization: Determine the spatial location of objects within the video frame, potentially enabling tasks like object counting or density estimation.
Audio Analysis: Analyze audio content within the video, such as identifying background sounds, music, or speech patterns.
Event Detection: Detect specific events or occurrences within the video, such as accidents, crowds, celebrations, or anomalies.
Sentiment Analysis: Analyze the overall sentiment or mood conveyed by the video content, based on visual and audio cues.
Content Summarization: Automatically generate summaries or highlights of the video content, highlighting key moments or segments.
Video Enhancement: Enhance the quality of the video by adjusting parameters like brightness, contrast, or stabilization.
Image Specification
Object Detection and Recognition: Identify and label objects present in the image, such as cars, people, animals, or household items.
Image Classification: Categorize images into predefined classes or categories, such as identifying whether an image contains a cat or a dog.
Semantic Segmentation: Segment the image into different regions and assign a label to each region based on its semantic meaning. For example, separating foreground objects from the background.
Text Detection and Recognition: Identify and extract text from images, which can be useful for tasks like reading license plates, recognizing handwritten notes, or extracting information from documents.
Facial Recognition: Identify and recognize faces in the image, potentially matching them against a database of known individuals.
Scene Understanding: Understand the overall context or scene depicted in the image, such as whether it's indoor or outdoor, daytime or nighttime, and the general activities or events taking place.
Image Quality Assessment: Assess the quality of the image, including factors like resolution, brightness, contrast, and sharpness.
Image Enhancement: Automatically enhance the quality of the image by adjusting parameters like brightness, contrast, and color balance.
Image Similarity and Search: Compare the image with a database of other images to find similar or visually related images.
Metadata Extraction: Extract metadata embedded in the image file, such as location information, camera settings, and timestamps.
Anomaly Detection: Identify unusual or abnormal patterns within the image that may indicate potential problems or anomalies.
The text was updated successfully, but these errors were encountered:
namwanza
changed the title
What I would like to see in videos and images?
[Feature] Ability to search for images and videos.
Apr 20, 2024
I should be able to search for videos or images, e.g. by the title of the image or video, by geo-coordinates, also with the context of the video and so on.
When I use nesis to analyse videos, I want the following types of information to be extracted or analysed, depending on my goals or application. Here are some common types of information I want nesis to output from the videos and images:
Object Detection and Tracking: Identify and track objects or people within the video frame over time. This could include detecting vehicles, pedestrians, animals, or specific objects of interest.
Action Recognition: Recognize human actions or activities depicted in the video, such as walking, running, sitting, or gestures.
Facial Recognition: Identify and recognize faces of individuals appearing in the video, potentially matching them against a database of known individuals.
Emotion Recognition: Analyze facial expressions to infer the emotional state of individuals within the video, such as happiness, sadness, anger, or surprise.
Speech Recognition and Transcription: Convert spoken words within the video into text, enabling transcription and analysis of dialogue or speech content.
Scene Understanding: Understand the overall context or scene depicted in the video, such as indoor or outdoor settings, specific locations, or environmental conditions.
Object Localization: Determine the spatial location of objects within the video frame, potentially enabling tasks like object counting or density estimation.
Audio Analysis: Analyze audio content within the video, such as identifying background sounds, music, or speech patterns.
Event Detection: Detect specific events or occurrences within the video, such as accidents, crowds, celebrations, or anomalies.
Sentiment Analysis: Analyze the overall sentiment or mood conveyed by the video content, based on visual and audio cues.
Content Summarization: Automatically generate summaries or highlights of the video content, highlighting key moments or segments.
Video Enhancement: Enhance the quality of the video by adjusting parameters like brightness, contrast, or stabilization.
Object Detection and Recognition: Identify and label objects present in the image, such as cars, people, animals, or household items.
Image Classification: Categorize images into predefined classes or categories, such as identifying whether an image contains a cat or a dog.
Semantic Segmentation: Segment the image into different regions and assign a label to each region based on its semantic meaning. For example, separating foreground objects from the background.
Text Detection and Recognition: Identify and extract text from images, which can be useful for tasks like reading license plates, recognizing handwritten notes, or extracting information from documents.
Facial Recognition: Identify and recognize faces in the image, potentially matching them against a database of known individuals.
Scene Understanding: Understand the overall context or scene depicted in the image, such as whether it's indoor or outdoor, daytime or nighttime, and the general activities or events taking place.
Image Quality Assessment: Assess the quality of the image, including factors like resolution, brightness, contrast, and sharpness.
Image Enhancement: Automatically enhance the quality of the image by adjusting parameters like brightness, contrast, and color balance.
Image Similarity and Search: Compare the image with a database of other images to find similar or visually related images.
Metadata Extraction: Extract metadata embedded in the image file, such as location information, camera settings, and timestamps.
Anomaly Detection: Identify unusual or abnormal patterns within the image that may indicate potential problems or anomalies.
The text was updated successfully, but these errors were encountered: