kamelets.djl-image-to-text-action.kamelet.yaml Maven / Gradle / Ivy
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# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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# ---------------------------------------------------------------------------
apiVersion: camel.apache.org/v1
kind: Kamelet
metadata:
name: djl-image-to-text-action
annotations:
camel.apache.org/kamelet.support.level: "Preview"
camel.apache.org/catalog.version: "4.8.0"
camel.apache.org/kamelet.icon: "data:image/png;base64,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"
camel.apache.org/provider: "Apache Software Foundation"
camel.apache.org/kamelet.group: "Actions"
camel.apache.org/kamelet.namespace: "AI"
labels:
camel.apache.org/kamelet.type: "action"
spec:
definition:
title: "Image-to-Text Action"
description: Detect and classify objects in an image into texts using the SSD and ResNet models and the ImageNet dataset.
type: object
types:
out:
mediaType: application/json
dependencies:
- "mvn:ai.djl.pytorch:pytorch-engine:0.29.0"
- "mvn:ai.djl.pytorch:pytorch-model-zoo:0.29.0"
- "mvn:net.sf.extjwnl:extjwnl:2.0.5"
- "mvn:net.sf.extjwnl:extjwnl-data-wn31:1.2"
- "mvn:org.apache.camel.kamelets:camel-kamelets-utils:4.8.0"
- "camel:core"
- "camel:kamelet"
- "camel:jackson"
- "camel:djl"
template:
beans:
- name: imageNetUtil
type: "#class:org.apache.camel.kamelets.utils.djl.ImageNetUtil"
from:
uri: "kamelet:source"
steps:
- to: "djl:cv/object_detection?artifactId=ssd"
- convertBodyTo: "ai.djl.modality.cv.Image[]"
- split:
expression:
simple: "${body}"
aggregationStrategy: "#class:org.apache.camel.processor.aggregate.GroupedBodyAggregationStrategy"
steps:
- to: "djl:cv/image_classification?artifactId=resnet"
# The output from the image classification model is classified
# as one of 1000 labels from WordNet.
# Since it's too fine-grained, we want to find the higher-level
# group (= hypernym) for the classification using the WordNet
# dictionary.
- bean:
ref: "{{imageNetUtil}}"
method: extractClassName
- bean:
ref: "{{imageNetUtil}}"
method: addHypernym
- marshal:
json: {}