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44d8cdbba1
* ROCm AMD/GPU based build and detector, WIP * detectors/rocm: separate yolov8 postprocessing into own function; fix box scaling; use cv2.dnn.blobForImage for preprocessing; assert on required model parameters * AMD/ROCm: add couple of more ultralytics models; comments * docker/rocm: make imported model files readable by all * docker/rocm: readme about running on AMD GPUs * docker/rocm: updated README * docker/rocm: updated README * docker/rocm: updated README * detectors/rocm: separated preprocessing functions into yolo_utils.py * detector/plugins: added onnx cpu plugin * docker/rocm: updated container with limite label sets * example detectors view * docker/rocm: updated README.md * docker/rocm: update README.md * docker/rocm: do not set HSA_OVERRIDE_GFX_VERSION at all for the general version as the empty value broke rocm * detectors: simplified/optimized yolov8_postprocess * detector/yolo_utils: indentation, remove unused variable * detectors/rocm: default option to conserve cpu usage at the expense of latency * detectors/yolo_utils: use nms to prefilter overlapping boxes if too many detected * detectors/edgetpu_tfl: add support for yolov8 * util/download_models: script to download yolov8 model files * docker/main: add download-models overlay into s6 startup * detectors/rocm: assume models are in /config/model_cache/yolov8/ * docker/rocm: compile onnx files into mxr files at startup * switch model download into bash script * detectors/rocm: automatically override HSA_OVERRIDE_GFX_VERSION for couple of known chipsets * docs: rocm detector first notes * typos * describe builds (harakas temporary) * docker/rocm: also build a version for gfx1100 * docker/rocm: use cp instead of tar * docker.rocm: remove README as it is now in detector config * frigate/detectors: renamed yolov8_preprocess->preprocess, pass input tensor element type * docker/main: use newer openvino (2023.3.0) * detectors: implement class aggregation * update yolov8 model * add openvino/yolov8 support for label aggregation * docker: remove pointless s6/timeout-up files * Revert "detectors: implement class aggregation" This reverts commitdcfe6bbf6f. * detectors/openvino: remove class aggregation * detectors: increase yolov8 postprocessing score trershold to 0.5 * docker/rocm: separate rocm distributed files into its own build stage * Update object_detectors.md * updated CODEOWNERS file for rocm * updated build names for documentation * Revert "docker/main: use newer openvino (2023.3.0)" This reverts commitdee95de908. * reverrted openvino detector * reverted edgetpu detector * scratched rocm docs from any mention of edgetpu or openvino * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * renamed frigate.detectors.yolo_utils.py -> frigate.detectors.util.py * clarified rocm example performance * Improved wording and clarified text * Mentioned rocm detector for AMD GPUs * applied ruff formating * applied ruff suggested fixes * docker/rocm: fix missing argument resulting in larger docker image sizes * docs/configuration/object_detectors: fix links to yolov8 release files --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
35 lines
1.3 KiB
Plaintext
Executable File
35 lines
1.3 KiB
Plaintext
Executable File
#!/command/with-contenv bash
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# shellcheck shell=bash
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# Download yolov8 models when DOWNLOAD_YOLOV8=1 environment variable is set
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set -o errexit -o nounset -o pipefail
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MODEL_CACHE_DIR=${MODEL_CACHE_DIR:-"/config/model_cache"}
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YOLOV8_DIR="$MODEL_CACHE_DIR/yolov8"
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YOLOV8_URL=https://github.com/harakas/models/releases/download/yolov8.1-1.1/yolov8.small.models.tar.gz
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YOLOV8_DIGEST=304186b299560fbacc28eac9b9ea02cc2289fe30eb2c0df30109a2529423695c
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if [ "$DOWNLOAD_YOLOV8" = "1" ]; then
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echo "download-models: DOWNLOAD_YOLOV8=${DOWNLOAD_YOLOV8}, running download"
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if ! test -f "${YOLOV8_DIR}/model.fetched"; then
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mkdir -p $YOLOV8_DIR
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TMP_FILE="${YOLOV8_DIR}/download.tar.gz"
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curl --no-progress-meter -L --max-filesize 500M --insecure --output $TMP_FILE "${YOLOV8_URL}"
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digest=$(sha256sum $TMP_FILE | awk '{print $1}')
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if [ "$digest" = "$YOLOV8_DIGEST" ]; then
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echo "download-models: Extracting downloaded file"
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cd $YOLOV8_DIR
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tar zxf $TMP_FILE
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rm $TMP_FILE
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touch model.fetched
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echo "download-models: Yolov8 download done, files placed into ${YOLOV8_DIR}"
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else
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echo "download-models: Downloaded file digest does not match: got $digest, expected $YOLOV8_DIGEST"
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rm $TMP_FILE
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fi
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else
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echo "download-models: ${YOLOV8_DIR}/model.fetched already present"
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fi
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fi
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