Adding ClipDetection component code.

cpp/OcvYoloDetection/triton_server/Dockerfile

@@ -60,7 +60,7 @@ RUN --mount=type=tmpfs,target=/tmp \
     mv main /model-gen/yolo/gen-engine-608; \
     mv libyolo608layerplugin.so /plugins/libyolo608layerplugin.so
 
-COPY models/yolo-608.config.pbtxt /models/yolo-608/1/config.pbtxt
+COPY models/yolo-608.config.pbtxt /models/yolo-608/config.pbtxt
 
 COPY docker-entrypoint.sh /opt/tritonserver
 

python/ClipDetection/COPYING

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

@@ -0,0 +1,65 @@
+# 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 2023 The MITRE Corporation. All Rights Reserved.                #
+#############################################################################
+
+#############################################################################
+# Copyright 2023 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 MODELS_REGISTRY=openmpf/
+ARG BUILD_REGISTRY
+ARG BUILD_TAG=latest
+FROM ${MODELS_REGISTRY}openmpf_clip_detection_models:7.2.0 as models
+FROM ${BUILD_REGISTRY}openmpf_python_executor_ssb:${BUILD_TAG}
+
+COPY --from=models /models/ViT-B-32.pt /models/ViT-B-32.pt
+
+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 ftfy regex tqdm
+
+RUN --mount=type=tmpfs,target=/tmp \
+        mkdir /tmp/CLIP; \
+        wget -O- 'https://github.com/openai/CLIP/tarball/master' \
+            | tar --extract --gzip --directory /tmp/CLIP; \
+        cd /tmp/CLIP/*; \
+        pip3 install . 'torchvision==0.8.2'
+
+ARG RUN_TESTS=false
+
+RUN --mount=target=.,readwrite \
+    install-component.sh; \
+    if [ "${RUN_TESTS,,}" == true ]; then python tests/test_clip.py; fi
+
+LABEL org.label-schema.license="Apache 2.0" \
+      org.label-schema.name="OpenMPF CLIP 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/ClipDetection/LICENSE

@@ -0,0 +1,32 @@
+/******************************************************************************
+* Copyright 2023 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:
+
+--------------------------------------------------------------------------
+
+The TensorFlow implementation of the Contrastive Language-Image 
+Pre-Training (CLIP) model used by this component was developed by OpenAI:
+http://www.github.com/openai/CLIP
+
+The OpenAI CLIP model is licensed under the MIT License.

python/ClipDetection/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 2023 The MITRE Corporation. All Rights Reserved.