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# TorchServe default inference handlers | ||
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TorchServe provides following inference handlers out of box : | ||
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## image_classifier | ||
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* Description : Handles image classification models trained on imagenet dataset. | ||
* Input : RGB image | ||
* Output : Top 5 predictions and their respective probability of the image | ||
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For more details refer [examples](../examples/image_classifier) | ||
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## image_segmenter | ||
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* Description : Handles image segmentation models trained on imagenet dataset. | ||
* Input : RGB image | ||
* Output : Output shape as [CL H W], CL - number of classes, H - height and W - width. | ||
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For more details refer [examples](../examples/image_segmenter) | ||
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## object_detector | ||
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* Description : Handles object detection models. | ||
* Input : RGB image | ||
* Output : List of detected classes and bounding boxes respectively | ||
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For more details refer [examples](../examples/object_detector) | ||
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## text_classifier | ||
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* Description : Handles models trained on imagenet dataset. | ||
* Input : text file | ||
* Output : Class of input text | ||
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For more details refer [examples](../examples/text_classification) | ||
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