A classifier classifies an input (such as an entire image or sentence of text) into different categories. It assigns a confidence score for each class. Hive’s classifier models include the visual classification models and text classification models.
Classification models can be multi-headed, where each group of mutually exclusive model classes belong to a single model head. For example, when an image is run through Hive's visual moderation model, one head might classify sexually not-safe-for-work (NSFW) content while another head might classify the presence of guns.
This concept is illustrated below. This imaginary model has two heads:
- NSFW classification: general_nsfw, general_suggestive, general_not_nsfw_not_suggestive
- Gun classification: gun_in_hand, animated_gun, gun_not_in_hand, no_gun
The confidence scores for each model head sum to 1.
{
"output": [
{
"time": 0,
"classes": [
{
"class": "general_nsfw",
"score": 0.9
},
{
"class": "general_suggestive",
"score": 0.05
},
{
"class": "general_not_nsfw_not_suggestive",
"score": 0.05
},
{
"class": "gun_in_hand",
"score": 0.88
},
{
"class": "animated_gun",
"score": 0.04
},
{
"class": "gun_not_in_hand",
"score": 0.04
},
{
"class": "no_gun",
"score": 0.04
}
]
}
]
}
Name | Description |
---|---|
time | Timestamp in seconds of video or audio frame extracted from the original media. Always 0 for images |
classes | List of objects for each output class that the API predicts. |
class | Name of predicted class. |
score | Confidence score of predicted class. |