Create LlavaDetection component

python/ClipDetection/Dockerfile

@@ -29,7 +29,7 @@
 ARG MODELS_REGISTRY=openmpf/
 ARG BUILD_REGISTRY
 ARG BUILD_TAG=latest
-FROM ${MODELS_REGISTRY}openmpf_clip_detection_models:8.0.0 as models
+FROM ${MODELS_REGISTRY}openmpf_clip_detection_models:9.0.0 as models
 FROM ${BUILD_REGISTRY}openmpf_python_executor_ssb:${BUILD_TAG}
 
 COPY --from=models /models/ViT-B-32.pt /models/ViT-B-32.pt

python/LlavaDetection/COPYING

@@ -0,0 +1,175 @@
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python/LlavaDetection/Dockerfile

@@ -0,0 +1,54 @@
+# syntax=docker/dockerfile:experimental
+
+#############################################################################
+# NOTICE                                                                    #
+#                                                                           #
+# This software (or technical data) was produced for the U.S. Government    #
+# under contract, and is subject to the Rights in Data-General Clause       #
+# 52.227-14, Alt. IV (DEC 2007).                                            #
+#                                                                           #
+# Copyright 2024 The MITRE Corporation. All Rights Reserved.                #
+#############################################################################
+
+#############################################################################
+# Copyright 2024 The MITRE Corporation                                      #
+#                                                                           #
+# Licensed 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       #
+# limitations under the License.                                            #
+#############################################################################
+
+ARG BUILD_REGISTRY
+ARG BUILD_TAG=latest
+FROM ${BUILD_REGISTRY}openmpf_python_executor_ssb:${BUILD_TAG}
+
+RUN --mount=type=tmpfs,target=/var/cache/apt \
+    --mount=type=tmpfs,target=/var/lib/apt/lists  \
+    --mount=type=tmpfs,target=/tmp \
+    apt-get update; \
+    DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y wget
+
+RUN pip3 install --upgrade pip
+
+RUN pip3 install opencv-python ollama
+
+ARG RUN_TESTS=false
+
+RUN --mount=target=.,readwrite \
+    install-component.sh; \
+    if [ "${RUN_TESTS,,}" == true ]; then python tests/test_llava.py; fi
+
+LABEL org.label-schema.license="Apache 2.0" \
+      org.label-schema.name="OpenMPF LLaVA Detection" \
+      org.label-schema.schema-version="1.0" \
+      org.label-schema.url="https://openmpf.github.io" \
+      org.label-schema.vcs-url="https://github.com/openmpf/openmpf-components" \
+      org.label-schema.vendor="MITRE"

python/LlavaDetection/LICENSE

@@ -0,0 +1,27 @@
+/******************************************************************************
+* Copyright 2024 The MITRE Corporation                                       *
+*                                                                            *
+* Licensed 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        *
+* limitations under the License.                                             *
+******************************************************************************/
+
+This project contains content developed by The MITRE Corporation. If this code
+is used in a deployment or embedded within another project, it is requested
+that you send an email to opensource@mitre.org in order to let us know where
+this software is being used.
+
+
+
+This software makes use of a data model derived from third party software:
+
+--------------------------------------------------------------------------
+

python/LlavaDetection/NOTICE

@@ -0,0 +1,7 @@
+# NOTICE
+
+This software (or technical data) was produced for the U.S. Government 
+under contract, and is subject to the Rights in Data-General Clause 
+552.227-14, Alt. IV (DEC 2007).
+
+Copyright 2024 The MITRE Corporation. All Rights Reserved.

python/LlavaDetection/README.md

@@ -0,0 +1,86 @@
+# Overview
+
+This repository contains source code for the OpenMPF LLaVA Detection Component.
+
+This component utilizes a config file that contains any number of prompts for any number of object classes. These prompts and the images/video frames are passed to an instance of the [LLaVA 34b](https://huggingface.co/liuhaotian/llava-v1.6-34b) model within [Ollama](https://ollama.com) to generate responses.
+
+The component is built to support multi-stage pipelines where feed forward tracks from an object detector component are passed in to be queried further. The user can specify custom classes and prompts that coincide with the classes of objects being passed into the component.
+
+# Job Properties
+
+The following are the properties that can be specified for the component. Each property has a default value and so none of them necessarily need to be specified for processing jobs.
+
+- `PROMPT_CONFIGURATION_PATH`: Specifies the file path to the prompt config file.
+- `JSON_PROMPT_CONFIGURATION_PATH`: Specifies the file path to the JSON output prompt config file.
+- `ENABLE_JSON_PROMPT_FORMAT`: Boolean that enables JSON outputs.
+- `OLLAMA_SERVER`: The Ollama server `<host>`:`<port>` to use for inferencing.
+- `GENERATE_FRAME_RATE_CAP`: Specifies the maximum number of frames to process every second.
+
+# Config File
+
+The config file is a JSON formatted file that is used by the component to know which prompts to ask LLaVA depending on the class of the object. The user can write their own config file and can be used by setting the `PROMPT_CONFIGURATION_PATH` property. The following is an example of the proper syntax to follow:
+
+```json
+[
+    {
+        "classes": [
+            "DOG",
+            "CAT",
+            "HORSE"
+        ],
+        "prompts": [
+            {
+                "detectionProperty": "DESCRIPTION",
+                "prompt": "Describe the animal's color and appearance."
+            }
+        ]
+    },
+    {
+        "classes": [
+            "DOG"
+        ],
+        "prompts": [
+            {
+                "detectionProperty": "DOG BREED",
+                "prompt": "Describe the potential breeds that this dog could contain."
+            }
+        ]
+    }
+]
+```
+
+Note that a class can appear in multiple entries in the JSON, such as `"DOG"` in the example. If you have multiple classes that share a prompt, you can list them together like above and then add more questions for each individual class if you wish to get more specific. 
+
+Also be sure to make each `"detectionProperty"` distinct for a given class so that none of your prompts are overwritten.
+
+# JSON Config File
+
+The JSON config file allows you to specify that LLaVA returns a JSON object as output where you can specify the fields that the model should fill out. The user can write their own config file and can be used by setting the `JSON_PROMPT_CONFIGURATION_PATH` property. The following is an example of the proper syntax to follow:
+
+
+```json
+{
+    "classPrompts": [
+        {
+            "classes": [
+                "DOG"
+            ],
+            "prompts": [
+                "Describe the dog in JSON. The JSON should have the following keys: breed, color, size."
+            ]
+        },
+        {
+            "classes": [
+                "PERSON"
+            ],
+            "prompts": [
+                "Describe the person in JSON. The JSON should have the following keys: hair_color (if unsure, respond with unsure), clothes, activity."
+            ]
+        }
+    ]
+}
+```
+
+# Outputs
+
+Once the responses are generated, they are added onto the `detection_properties` dictionary of the associated `ImageLocation` object. for each prompt, the key is specified by the `"detectionProperty"` field of the config JSON and the value will be the LLaVA-generated response.